Requis

requis

Christian Science by Mark Twain, is part of the HackerNoon Books Series. You can jump to any chapter in this book . HONESTY REQUISITE here HONESTY REQUISITE Dishonest members are to be admonished; if they continue in dishonest practices, excommunication follows. Considering who it is that draughted this law, there is a certain amount of humor in it. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Mark Twain (2004). Christian Science. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/3187/pg3187-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

HONESTY REQUISITE

credit: http://saphanatutorial.com/prerequisites-for-learning-sap-hana/ I’m writing this post to jot down all the things I need to do during website deployments. cloudy ASP.NET Get the database connector project Re- Publish Grab that awesome URL rewrite module Set and free IIS_IUSRS app pool Check that your application pool refers to correct version of .NET Get — obviously it’s a new server, right? re-certified and certificate Import install the same in Import IIS Originally published at xameeramir.github.io .

What are the pre-requisites for an ASP.NET website launch

Authors:
(1) Xian Liu, Snap Inc., CUHK with Work done during an internship at Snap Inc.;
(2) Jian Ren, Snap Inc. with Corresponding author: jren@snapchat.com;
(3) Aliaksandr Siarohin, Snap Inc.;
(4) Ivan Skorokhodov, Snap Inc.;
(5) Yanyu Li, Snap Inc.;
(6) Dahua Lin, CUHK;
(7) Xihui Liu, HKU;
(8) Ziwei Liu, NTU;
(9) Sergey Tulyakov, Snap Inc. Table of Links Abstract and 1 Introduction 2 Related Work 3 Our Approach and 3.1 Preliminaries and Problem Setting 3.2 Latent Structural Diffusion Model 3.3 Structure-Guided Refiner 4 Human Verse Dataset 5 Experiments 5.1 Main Results 5.2 Ablation Study 6 Discussion and References A Appendix and A.1 Additional Quantitative Results A.2 More Implementation Details and A.3 More Ablation Study Results A.4 More User Study Details A.5 Impact of Random Seed and Model Robustness and A.6 Boarder Impact and Ethical Consideration A.7 More Comparison Results and A.8 Additional Qualitative Results A.9 Licenses 3 OUR APPROACH We present HyperHuman that generates in-the-wild human images of high realism and diverse layouts. The overall framework is illustrated in Fig. 2. To make the content self-contained and narration clearer, we first introduce some pre-requisites of diffusion models and the problem setting in Sec. 3.1. Then, we present the Latent Structural Diffusion Model which simultaneously denoises the depth, surface-normal along with the RGB image. The explicit appearance and latent structure are thus jointly learned in a unified model (Sec. 3.2). Finally, we elaborate the Structure-Guided Refiner to compose the predicted conditions for detailed generation of higher resolution in Sec. 3.3. 3.1 PRELIMINARIES AND PROBLEM SETTING During inference, only the text prompt and body skeleton are needed to synthesize well-aligned RGB image, depth, and surface-normal. Note that the users are free to substitute their own depth and surface-normal conditions to G2 if applicable, enabling more flexible and controllable generation This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Xian Liu, Snap Inc., CUHK with Work done during an internship at Snap Inc.; (2) Jian Ren, Snap Inc. with Corresponding author: jren@snapchat.com; (3) Aliaksandr Siarohin, Snap Inc.; (4) Ivan Skorokhodov, Snap Inc.; (5) Yanyu Li, Snap Inc.; (6) Dahua Lin, CUHK; (7) Xihui Liu, HKU; (8) Ziwei Liu, NTU; (9) Sergey Tulyakov, Snap Inc. Authors: Authors: (1) Xian Liu, Snap Inc., CUHK with Work done during an internship at Snap Inc.; (2) Jian Ren, Snap Inc. with Corresponding author: jren@snapchat.com; (3) Aliaksandr Siarohin, Snap Inc.; (4) Ivan Skorokhodov, Snap Inc.; (5) Yanyu Li, Snap Inc.; (6) Dahua Lin, CUHK; (7) Xihui Liu, HKU; (8) Ziwei Liu, NTU; (9) Sergey Tulyakov, Snap Inc. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Work 2 Related Work 3 Our Approach and 3.1 Preliminaries and Problem Setting 3 Our Approach and 3.1 Preliminaries and Problem Setting 3.2 Latent Structural Diffusion Model 3.2 Latent Structural Diffusion Model 3.3 Structure-Guided Refiner 3.3 Structure-Guided Refiner 4 Human Verse Dataset 4 Human Verse Dataset 5 Experiments 5 Experiments 5.1 Main Results 5.1 Main Results 5.2 Ablation Study 5.2 Ablation Study 6 Discussion and References 6 Discussion and References A Appendix and A.1 Additional Quantitative Results A Appendix and A.1 Additional Quantitative Results A.2 More Implementation Details and A.3 More Ablation Study Results A.2 More Implementation Details and A.3 More Ablation Study Results A.4 More User Study Details A.4 More User Study Details A.5 Impact of Random Seed and Model Robustness and A.6 Boarder Impact and Ethical Consideration A.5 Impact of Random Seed and Model Robustness and A.6 Boarder Impact and Ethical Consideration A.7 More Comparison Results and A.8 Additional Qualitative Results A.7 More Comparison Results and A.8 Additional Qualitative Results A.9 Licenses A.9 Licenses 3 OUR APPROACH We present HyperHuman that generates in-the-wild human images of high realism and diverse layouts. The overall framework is illustrated in Fig. 2. To make the content self-contained and narration clearer, we first introduce some pre-requisites of diffusion models and the problem setting in Sec. 3.1. Then, we present the Latent Structural Diffusion Model which simultaneously denoises the depth, surface-normal along with the RGB image. The explicit appearance and latent structure are thus jointly learned in a unified model (Sec. 3.2). Finally, we elaborate the Structure-Guided Refiner to compose the predicted conditions for detailed generation of higher resolution in Sec. 3.3. 3.1 PRELIMINARIES AND PROBLEM SETTING During inference, only the text prompt and body skeleton are needed to synthesize well-aligned RGB image, depth, and surface-normal. Note that the users are free to substitute their own depth and surface-normal conditions to G2 if applicable, enabling more flexible and controllable generation This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

A Unified Approach to In-The-Wild Realistic Human Image Generation

How to Manage Permissions in a Langflow Chain for LLM Queries Using Permit.io

Is a Green Build and Fixing Flaky Tests Your #1 Priority? I recently had a discussion with the founder of a CI delivery platform about the value of fixing flaky tests, and it led to the following observation/question on LinkedIn: “Over my career, I’ve been in maybe 50 software development teams as an IC. In my current role, I get exposed to 10,000+. If I picked a random person across my entire sample set, they wouldn’t even know where to start with ‘doing the right thing.’ I see way more disengaged engineers who have a ‘give me a ticket and I’ll give you code’ mindset. How would you go about rebooting that?” It’s a great question. I thought I’d write about how we’ve approached this in my last two companies. It’s easy to say that culture is the answer, but how do you build that culture? How do you get every member of the team to care about doing the right thing — and what is the right thing? So Many Priority #1s It often feels that everything is a top priority. But that, in itself, is part of the problem. Particularly in start-ups and scale-ups, Engineering and Product teams experience immense pressure to deliver. This pressure is often self-imposed - at most of my previous companies, stakeholders were generally willing to accept a temporary slowdown for a long-term increase in quality. Here’s the thing: achieving a stable environment with few bugs takes time, but once you’re there, you can actually deliver faster and more efficiently. With so much emphasis on features and delivery, it’s no wonder engineers feel torn between addressing quality and stability issues or pushing out new features. So, how do you approach this? While the question of priority is nuanced and will vary from company to company, here’s a list of priorities based on my recent experiences. 1. Build a Culture of Ownership and Accountability Building a culture of ownership takes time. Like any change, it requires repetition and reinforcement. Start immediately, as this will form the foundation for the following priorities. 2. Record, Prioritize, and Monitor Production Bugs and Defects It’s surprising how often teams fail to record and prioritize production issues. At UberCarshare, we had a successful product but no way to track bug count or severity. Once you record your production issues, you can start measuring and reporting them. This opens up meaningful conversations with stakeholders about the trade-offs between quality, stability, and new features. 3. Complete Root Cause Analysis (RCA) or Incident Reports for Significant Production Issues This complements the previous item and is a fundamental pillar of creating a culture of transparency, accountability, and autonomy. RCAs should be blameless: a celebration of transparency, learning, and self-improvement. When engineers feel comfortable writing RCA’s and see that transparency and accountability do not mean blame or punishment, they will feel a greater level of psychological safety. Tech debt is the root cause of many issues, and while we can’t fix everything immediately, completing RCAs and prioritizing follow-ups against other work is a major step toward prioritizing stability and quality over new features. 4. Establish a Continuous Green Build in CI I recognize there is an argument that this is a pre-requisite to any of the above but, like I said, it’s nuanced 🤷‍♂️, and a lot of this stuff can happen in parallel. In both of my previous companies, a flaky, unstable CI had become the norm, which is common in teams trying to scale quickly. You cannot overstate how expensive this is in terms of its impact on productivity, but when there is unclear ownership and accountability, it can be hard to know where to start in fixing it. Getting to a stable build can be a significant effort and may require dedicated resources. Our approach was as follows: Get the build consistently green and fast enough — exclude flaky tests as necessary! Address performance or timeout issues through sufficient resourcing and parallelization of tests.


Clarify and assign ownership of the excluded flaky tests — the squads owning them can decide whether they need to be fixed and reintroduced. Maintain zero tolerance for flaky tests: if tests become flaky, exclude them from the build until they are fixed 5. Monitoring System Health and Actually Caring About Your Logs It’s easy to set up error logging and reporting. However, getting your team to care about the logs and respond to them in real-time is far more challenging. Like performance and broken builds, system health needs to be a whole team effort and cannot be left to a DX, DevOps, or maintenance squad. System health relies on culture as much as anything else and once again requires a zero-tolerance approach. Agree on your tolerance thresholds with the team, ensure that alerts for exceeded thresholds are sent to a public channel, and set an expectation that no one in the team is allowed to walk by a problem. At Carshare, we established an expectation that no one should push an alert further into history by adding a new comment below without first ensuring someone was investigating the issue. Use These Principles to Drive a Culture of Autonomy and Accountability Document these principles and ways of working, workshop with the team on how best to implement them, share them with your product team and stakeholders, and then demand continuous improvement from your team. RCAs, error alerts, and broken builds should be attended to without prompting. Initially, you may need to prompt, nag, coach, and mentor your team. Above all, reassure them that fixing alerts, broken builds, or bugs really is their highest priority. Eventually, these issues will start to solve themselves, and productivity and output improvements will follow the noticeable improvement in quality and stability. Rinse and Repeat: The Path to Continuous Improvement The five priorities I’ve outlined are just the beginning. Continuous improvement should be ingrained in your process, and there will be many things to perfect: writing efficient tests
improving build speed
reducing handoffs
shifting quality left
improved collaboration with partners such as product and design teams
measuring quality, uptime, and cycle time
etc. Originally published at https://medium.com/vertical-slice/getting-software-engineers-to-do-the-right-thing-d42a0b923408 Is a Green Build and Fixing Flaky Tests Your #1 Priority? I recently had a discussion with the founder of a CI delivery platform about the value of fixing flaky tests, and it led to the following observation/question on LinkedIn: “Over my career, I’ve been in maybe 50 software development teams as an IC. In my current role, I get exposed to 10,000+. If I picked a random person across my entire sample set, they wouldn’t even know where to start with ‘doing the right thing.’ I see way more disengaged engineers who have a ‘give me a ticket and I’ll give you code’ mindset. How would you go about rebooting that?” “Over my career, I’ve been in maybe 50 software development teams as an IC. In my current role, I get exposed to 10,000+. If I picked a random person across my entire sample set, they wouldn’t even know where to start with ‘doing the right thing.’ I see way more disengaged engineers who have a ‘give me a ticket and I’ll give you code’ mindset. How would you go about rebooting that?” “Over my career, I’ve been in maybe 50 software development teams as an IC. In my current role, I get exposed to 10,000+. If I picked a random person across my entire sample set, they wouldn’t even know where to start with ‘doing the right thing.’ I see way more disengaged engineers who have a ‘give me a ticket and I’ll give you code’ mindset. How would you go about rebooting that?” It’s a great question. I thought I’d write about how we’ve approached this in my last two companies. It’s easy to say that culture is the answer, but how do you build that culture? How do you get every member of the team to care about doing the right thing — and what is the right thing ? right thing So Many Priority #1s It often feels that everything is a top priority. But that, in itself, is part of the problem. Particularly in start-ups and scale-ups, Engineering and Product teams experience immense pressure to deliver. This pressure is often self-imposed - at most of my previous companies, stakeholders were generally willing to accept a temporary slowdown for a long-term increase in quality. Here’s the thing: achieving a stable environment with few bugs takes time, but once you’re there, you can actually deliver faster and more efficiently. With so much emphasis on features and delivery, it’s no wonder engineers feel torn between addressing quality and stability issues or pushing out new features. So, how do you approach this? While the question of priority is nuanced and will vary from company to company, here’s a list of priorities based on my recent experiences. 1. Build a Culture of Ownership and Accountability Building a culture of ownership takes time. Like any change, it requires repetition and reinforcement. Start immediately, as this will form the foundation for the following priorities. 2. Record, Prioritize, and Monitor Production Bugs and Defects It’s surprising how often teams fail to record and prioritize production issues. At UberCarshare, we had a successful product but no way to track bug count or severity. Once you record your production issues, you can start measuring and reporting them. This opens up meaningful conversations with stakeholders about the trade-offs between quality, stability, and new features. 3. Complete Root Cause Analysis (RCA) or Incident Reports for Significant Production Issues This complements the previous item and is a fundamental pillar of creating a culture of transparency, accountability, and autonomy. RCAs should be blameless: a celebration of transparency, learning, and self-improvement. When engineers feel comfortable writing RCA’s and see that transparency and accountability do not mean blame or punishment, they will feel a greater level of psychological safety. Tech debt is the root cause of many issues, and while we can’t fix everything immediately, completing RCAs and prioritizing follow-ups against other work is a major step toward prioritizing stability and quality over new features. 4. Establish a Continuous Green Build in CI I recognize there is an argument that this is a pre-requisite to any of the above but, like I said, it’s nuanced 🤷‍♂️, and a lot of this stuff can happen in parallel. In both of my previous companies, a flaky, unstable CI had become the norm, which is common in teams trying to scale quickly. You cannot overstate how expensive this is in terms of its impact on productivity, but when there is unclear ownership and accountability, it can be hard to know where to start in fixing it. Getting to a stable build can be a significant effort and may require dedicated resources. Our approach was as follows: Get the build consistently green and fast enough — exclude flaky tests as necessary! Address performance or timeout issues through sufficient resourcing and parallelization of tests. Clarify and assign ownership of the excluded flaky tests — the squads owning them can decide whether they need to be fixed and reintroduced. Get the build consistently green and fast enough — exclude flaky tests as necessary! Address performance or timeout issues through sufficient resourcing and parallelization of tests. Get the build consistently green and fast enough — exclude flaky tests as necessary! Address performance or timeout issues through sufficient resourcing and parallelization of tests. Clarify and assign ownership of the excluded flaky tests — the squads owning them can decide whether they need to be fixed and reintroduced. Clarify and assign ownership of the excluded flaky tests — the squads owning them can decide whether they need to be fixed and reintroduced. Maintain zero tolerance for flaky tests: if tests become flaky, exclude them from the build until they are fixed Maintain zero tolerance for flaky tests: if tests become flaky, exclude them from the build until they are fixed 5. Monitoring System Health and Actually Caring About Your Logs It’s easy to set up error logging and reporting. However, getting your team to care about the logs and respond to them in real-time is far more challenging. Like performance and broken builds, system health needs to be a whole team effort and cannot be left to a DX, DevOps, or maintenance squad. System health relies on culture as much as anything else and once again requires a zero-tolerance approach. Agree on your tolerance thresholds with the team, ensure that alerts for exceeded thresholds are sent to a public channel, and set an expectation that no one in the team is allowed to walk by a problem. At Carshare, we established an expectation that no one should push an alert further into history by adding a new comment below without first ensuring someone was investigating the issue. Use These Principles to Drive a Culture of Autonomy and Accountability Document these principles and ways of working, workshop with the team on how best to implement them, share them with your product team and stakeholders, and then demand continuous improvement from your team. RCAs, error alerts, and broken builds should be attended to without prompting. Initially, you may need to prompt, nag, coach, and mentor your team. Above all, reassure them that fixing alerts, broken builds, or bugs really is their highest priority. Eventually, these issues will start to solve themselves, and productivity and output improvements will follow the noticeable improvement in quality and stability. is Rinse and Repeat: The Path to Continuous Improvement The five priorities I’ve outlined are just the beginning. Continuous improvement should be ingrained in your process, and there will be many things to perfect: writing efficient tests improving build speed reducing handoffs shifting quality left improved collaboration with partners such as product and design teams measuring quality, uptime, and cycle time etc. writing efficient tests improving build speed reducing handoffs shifting quality left improved collaboration with partners such as product and design teams measuring quality, uptime, and cycle time etc. Originally published at https://medium.com/vertical-slice/getting-software-engineers-to-do-the-right-thing-d42a0b923408 https://medium.com/vertical-slice/getting-software-engineers-to-do-the-right-thing-d42a0b923408

How to Make Software Engineers Do the 'Right Thing'

100x Simpler -  The Ultimate Open-Source Guide

Financial institutions are investing heavily in AI, with North American banks leading the way in adopting gen AI for enhanced customer service and operational efficiency. The financial and banking services sector has entered a new phase in its digital transformation journey: the Artificial Intelligence (AI) era. While the use of AI in financial services is not new, and AI-powered applications such as trading algorithms and autonomous rule-based credit decision systems have been around for a while— the recent influx of capital from financial institutions to build future-proof AI infrastructure emphasizes the technology’s growing significance.According to a recentIDC report, the financial sector is projected to be the largest spender on AI solutions between 2024 and 2028, with banking at the forefront. The financial services industry is anticipated to account for over 20% of all AI expenditures, representing the highest growth rate among major industries. Today, AI's impact is evident across an array of financial applications, from automated knowledge management to personalized banking services. Specifically, North American banks are heavily investing in generative AI (genAI) to drive innovation and improve operational transparency. GenAI is helping enhance banking and chatbot capabilities, offering experiences that are distinct from traditional automated services. GenAI agents are now available 24/7 in multiple languages, to assist customers with banking queries and account management. To support these efforts, they are acquiring crucial hardware like AI chips and data processing infrastructure, while simultaneously channeling resources to hire human talent. Finance and AI: A Synergy in the Making Financial institutions are among the most data-rich organizations, handling billions of customer transactions and interactions across both digital and physical platforms. This wealth of data is essential to train A.I. systems, which is why banks have been pouring significant resources into maintaining the technology. The goal is to refine existing customer processes and explore high-impact use cases for inculcating A.I., scaling innovative prototypes into robust solutions. For instance, Paris-based Amundi, managing €2 trillion ($2.1 trillion) in assets, utilizes genAI tools to customize investment portfolios for its more than 100 million clients. By engaging clients in discussions about their risk preferences through its chatbot, the asset management firm crafts portfolios that meet individual needs while also gaining real-time insights into client sentiment. “Younger demographics, who will make up an increasingly large percentage of overall target customers for the finance industry - are very comfortable interacting with chatbots and often prefer this option over traditional options like call centers,” Ranjit Tinaikar, CEO of Ness Digital Engineering, told me. “AI can drastically improve the risk insights in pricing consumer loans. The banking industry is tapping into these trends to future-proof the way they deliver customer service and optimize experiences” Renowned North American investment bank and wealth management firm Morgan Stanley, recently introduced its new internal genAI model designed for its financial advisors and support staff. Powered by OpenAI’s GPT-4, the ‘AI @ Morgan Stanley Assistant’ helps thousands of wealth managers to swiftly retrieve information from an extensive internal knowledge base. It can also summarize client meeting notes and automatically draft follow-up emails. Despite its promise, the use of AI for handling sensitive financial decisions does have its drawbacks. AI models’ decision-making abilities are often hindered by unreliable data or unexpected infrastructural errors, which in turn impacts their effectiveness. Challenges and Limitations of AI in Financial Services A.I.'s ability to disrupt industry dynamics appears closely tied to the nature of customer data and the challenges it addresses. In banking service areas like wealth management or lending, where data is less abundant and unstable, A.I.'s impact has been more incremental than transformational. The finance industry’s experience with AI also raises questions about whether AI will democratize or consolidate power within the sector. “Most banking corporations don’t have the requisite organizational expertise and governance to deploy A.I. solutions. GenA.I. is only as smart as the data used to train the large language models (LLMs),” Tinaikar added. “Access to this data, which is often fragmented across internal and external systems, is a major challenge to create reliable financial A.I. models.” It is crucial to ensure that A.I. operates within a secure, ethical, and compliant framework to prevent potentially sensitive data misuse. In this context, larger companies with vast resources for technology and data investments hold a notable edge over their smaller rivals. For small and medium-sized businesses (SMBs), the real challenge to creating smarter and reliable A.I. systems is their inability to afford A.I. experts and invest in security management architectures. “You do need a “human-in-loop” for sensitive decisions around A.I.-generated pricing and risk recommendations,” said Tinaikar. “In the interim, SMB corporates have to develop their self-governance to protect their consumers, investors, and other key stakeholders.” Why Human Judgment Remains Crucial in AI-Enhanced Finance GenA.I. represents a transformative shift, enabling banks to fully harness the power of their customer data. By analyzing structured and unstructured data from diverse sources and understanding the relationships between them, it offers enhanced visibility and insights into both risks and opportunities within and beyond the bank. But, as AI makes data analysis more efficient and cost-effective, the role of human judgment becomes even more crucial. AI systems currently lack the nuance and creativity of human insight, making them unreliable for sensitive use cases. Although AI is an incredibly powerful tool, financial managers and institutions stand to gain the most from combining AI's power with unique human abilities. “The difference lies, of course, in the type of emotional judgment applied by human experts,” explained Tinaikar. “As AI introduces the potential for a disruptive shift where machines could replace human judgment, we need to develop regulatory and technological solutions to ensure that humans remain involved in mission-critical tasks where machine-simulated judgment may not be reliable.” Financial institutions are investing heavily in AI, with North American banks leading the way in adopting gen AI for enhanced customer service and operational efficiency. Financial institutions are investing heavily in AI, with North American banks leading the way in adopting gen AI for enhanced customer service and operational efficiency. The financial and banking services sector has entered a new phase in its digital transformation journey: the Artificial Intelligence (AI) era. While the use of AI in financial services is not new, and AI-powered applications such as trading algorithms and autonomous rule-based credit decision systems have been around for a while— the recent influx of capital from financial institutions to build future-proof AI infrastructure emphasizes the technology’s growing significance. According to a recent IDC report , the financial sector is projected to be the largest spender on AI solutions between 2024 and 2028, with banking at the forefront. The financial services industry is anticipated to account for over 20% of all AI expenditures, representing the highest growth rate among major industries. IDC report IDC report Today, AI's impact is evident across an array of financial applications, from automated knowledge management to personalized banking services. Specifically, North American banks are heavily investing in generative AI ( genAI ) to drive innovation and improve operational transparency. GenAI is helping enhance banking and chatbot capabilities, offering experiences that are distinct from traditional automated services. GenAI agents are now available 24/7 in multiple languages, to assist customers with banking queries and account management. genAI To support these efforts, they are acquiring crucial hardware like AI chips and data processing infrastructure, while simultaneously channeling resources to hire human talent. Finance and AI: A Synergy in the Making Finance and AI: A Synergy in the Making Financial institutions are among the most data-rich organizations, handling billions of customer transactions and interactions across both digital and physical platforms. This wealth of data is essential to train A.I. systems, which is why banks have been pouring significant resources into maintaining the technology. The goal is to refine existing customer processes and explore high-impact use cases for inculcating A.I., scaling innovative prototypes into robust solutions. For instance, Paris-based Amundi , managing €2 trillion ($2.1 trillion) in assets, utilizes genAI tools to customize investment portfolios for its more than 100 million clients. By engaging clients in discussions about their risk preferences through its chatbot, the asset management firm crafts portfolios that meet individual needs while also gaining real-time insights into client sentiment. Amundi Amundi “Younger demographics, who will make up an increasingly large percentage of overall target customers for the finance industry - are very comfortable interacting with chatbots and often prefer this option over traditional options like call centers,” Ranjit Tinaikar, CEO of Ness Digital Engineering, told me. “AI can drastically improve the risk insights in pricing consumer loans. The banking industry is tapping into these trends to future-proof the way they deliver customer service and optimize experiences” Renowned North American investment bank and wealth management firm Morgan Stanley, recently introduced its new internal genAI model designed for its financial advisors and support staff. Powered by OpenAI’s GPT-4, the ‘ AI @ Morgan Stanley Assistant ’ helps thousands of wealth managers to swiftly retrieve information from an extensive internal knowledge base. It can also summarize client meeting notes and automatically draft follow-up emails. AI @ Morgan Stanley Assistant AI @ Morgan Stanley Assistant Despite its promise, the use of AI for handling sensitive financial decisions does have its drawbacks. AI models’ decision-making abilities are often hindered by unreliable data or unexpected infrastructural errors, which in turn impacts their effectiveness. Challenges and Limitations of AI in Financial Services Challenges and Limitations of AI in Financial Services A.I.'s ability to disrupt industry dynamics appears closely tied to the nature of customer data and the challenges it addresses. In banking service areas like wealth management or lending, where data is less abundant and unstable, A.I.'s impact has been more incremental than transformational. The finance industry’s experience with AI also raises questions about whether AI will democratize or consolidate power within the sector. “Most banking corporations don’t have the requisite organizational expertise and governance to deploy A.I. solutions. GenA.I. is only as smart as the data used to train the large language models (LLMs),” Tinaikar added. “Access to this data, which is often fragmented across internal and external systems, is a major challenge to create reliable financial A.I. models.” It is crucial to ensure that A.I. operates within a secure, ethical, and compliant framework to prevent potentially sensitive data misuse. In this context, larger companies with vast resources for technology and data investments hold a notable edge over their smaller rivals. For small and medium-sized businesses (SMBs), the real challenge to creating smarter and reliable A.I. systems is their inability to afford A.I. experts and invest in security management architectures. “You do need a “human-in-loop” for sensitive decisions around A.I.-generated pricing and risk recommendations,” said Tinaikar. “In the interim, SMB corporates have to develop their self-governance to protect their consumers, investors, and other key stakeholders.” Why Human Judgment Remains Crucial in AI-Enhanced Finance GenA.I. represents a transformative shift, enabling banks to fully harness the power of their customer data. By analyzing structured and unstructured data from diverse sources and understanding the relationships between them, it offers enhanced visibility and insights into both risks and opportunities within and beyond the bank. But, as AI makes data analysis more efficient and cost-effective, the role of human judgment becomes even more crucial. AI systems currently lack the nuance and creativity of human insight, making them unreliable for sensitive use cases. Although AI is an incredibly powerful tool, financial managers and institutions stand to gain the most from combining AI's power with unique human abilities. “The difference lies, of course, in the type of emotional judgment applied by human experts,” explained Tinaikar. “As AI introduces the potential for a disruptive shift where machines could replace human judgment, we need to develop regulatory and technological solutions to ensure that humans remain involved in mission-critical tasks where machine-simulated judgment may not be reliable.”

AI is Taking Over Your Bank, and You Might Not Even Know It

SAN FRANCISCO, USA, October 31st, 2024/Chainwire/--Tony Vejseli, Figure Markets Holdings Inc., and GXD Labs, LLC (collectively “the Group”) today issued a statement to address recent developments following a meeting held on October 28 at White & Case’s Midtown Manhattan offices, where the Group met with the board of directors (the “Board”) and management team of Ionic Digital, Inc. (the “Company” or “Ionic”). The Group thanked White & Case for hosting the discussion but noted a need for clarification following the Company’s summary of the meeting in a press release, which they believe misrepresented several key points. In response to Ionic’s statement regarding its affirmation of “strong momentum” and its “laser-focus” on implementing its strategic initiatives, the Group raised concerns over the Board’s apparent lack of knowledge of core operating metrics. They highlighted that the Board appeared unprepared to discuss any aspects of its financial or operational performance, including by answering any of Mr. Vejseli’s questions as described in his post on X, leading to questions about the Company’s competitive position and valuation. The Group also expressed skepticism about Ionic’s ability to complete its audit, initially expected in early 2024 and now anticipated by Q1 2025 according to the Company, within the announced timeframe due to the apparent lack of available financial information, including the Company’s EBITDA and expenses. The Group indicated that alternative liquidity options for shareholders were discussed, yet they felt these options had not been fully explored or evaluated by the Board. The Group also raised concerns over Ionic’s contract with Hut 8, noting that, although it had presented a proposed solution, no alternative path forward was discussed by the Board or management. During the meeting, the Group outlined a proposed plan for refreshment of the Board, specifically suggesting the resignation of three current board members—Scott Duffy, Tom DiFiore, and Emmanuel Aidoo – to be replaced by three new, independent directors with the requisite experience and skill sets. The proposal, supported by a detailed presentation, emphasized the need for strategic and experienced leadership to better align the company’s actions with shareholder interests. Shareholders are encouraged to review the proposal and consider supporting a special meeting to vote on board changes. About Figure Markets Figure Markets is democratizing finance through blockchain. We’re building the exchange for everything - a decentralized custody marketplace for crypto, stocks, bonds, credit and more. We’re bringing best-in-class leverage, margining, and liquidity to our exchange, while offering our members extensive borrowing options and unique investment opportunities. Figure Markets puts our members in control of their assets and data, disintermediating legacy brokers, exchanges and lenders. Figure Markets is backed by leading venture capital firms and strategic partners, including Jump Crypto, Pantera, Distributed Global, Faction Lightspeed, NewForm Capital and CMT Digital. Figure Markets was founded by a seasoned team of entrepreneurs and operators from TradFi, fintech, and DeFi, including Mike Cagney and June Ou. Users can learn more at www.figuremarkets.com. Contact Director, Marketing Paula Machado Jackler Figure Markets press@figuremarkets.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here SAN FRANCISCO, USA, October 31st, 2024/Chainwire/--Tony Vejseli, Figure Markets Holdings Inc., and GXD Labs, LLC (collectively “the Group”) today issued a statement to address recent developments following a meeting held on October 28 at White & Case’s Midtown Manhattan offices, where the Group met with the board of directors (the “Board”) and management team of Ionic Digital, Inc. (the “Company” or “Ionic”). The Group thanked White & Case for hosting the discussion but noted a need for clarification following the Company’s summary of the meeting in a press release , which they believe misrepresented several key points. press release press release In response to Ionic’s statement regarding its affirmation of “strong momentum” and its “laser-focus” on implementing its strategic initiatives, the Group raised concerns over the Board’s apparent lack of knowledge of core operating metrics. They highlighted that the Board appeared unprepared to discuss any aspects of its financial or operational performance, including by answering any of Mr. Vejseli’s questions as described in his post on X, leading to questions about the Company’s competitive position and valuation. post post The Group also expressed skepticism about Ionic’s ability to complete its audit, initially expected in early 2024 and now anticipated by Q1 2025 according to the Company, within the announced timeframe due to the apparent lack of available financial information, including the Company’s EBITDA and expenses. The Group indicated that alternative liquidity options for shareholders were discussed, yet they felt these options had not been fully explored or evaluated by the Board. The Group also raised concerns over Ionic’s contract with Hut 8, noting that, although it had presented a proposed solution, no alternative path forward was discussed by the Board or management. During the meeting, the Group outlined a proposed plan for refreshment of the Board, specifically suggesting the resignation of three current board members—Scott Duffy, Tom DiFiore, and Emmanuel Aidoo – to be replaced by three new, independent directors with the requisite experience and skill sets. The proposal, supported by a detailed presentation, emphasized the need for strategic and experienced leadership to better align the company’s actions with shareholder interests. Shareholders are encouraged to review the proposal and consider supporting a special meeting to vote on board changes. review the proposal review the proposal About Figure Markets Figure Markets is democratizing finance through blockchain. We’re building the exchange for everything - a decentralized custody marketplace for crypto, stocks, bonds, credit and more. Figure Markets Figure Markets We’re bringing best-in-class leverage, margining, and liquidity to our exchange, while offering our members extensive borrowing options and unique investment opportunities. Figure Markets puts our members in control of their assets and data, disintermediating legacy brokers, exchanges and lenders. Figure Markets is backed by leading venture capital firms and strategic partners, including Jump Crypto, Pantera, Distributed Global, Faction Lightspeed, NewForm Capital and CMT Digital. Figure Markets was founded by a seasoned team of entrepreneurs and operators from TradFi, fintech, and DeFi, including Mike Cagney and June Ou. Users can learn more at www.figuremarkets.com . www.figuremarkets.com www.figuremarkets.com Contact Director, Marketing Paula Machado Jackler Figure Markets press@figuremarkets.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here

Tony Vejseli, Figure Markets And GXD Labs Provide Clarification, Met With Ionic Digital’s Board

Tony Vejseli, Figure Markets y GXD Labs brindan aclaraciones y se reúnen con la junta directiva de Ionic Digital

Tony Vejseli, Figuurimarkkinat ja GXD Labs tarjoavat selvennystä, tapasivat Ionic Digitalin hallituksen

टोनी वेजसेली, फिगर मार्केट्स और जीएक्सडी लैब्स ने स्पष्टीकरण दिया, आयनिक डिजिटल के बोर्ड से मुलाकात की

Tony Vejseli, Figure Markets ak GXD Labs bay klarifikasyon, te rankontre ak Konsèy Ionic Digital la

טוני Vejseli, Figure Markets ו-GXD Labs מספקים הבהרה, נפגשו עם מועצת המנהלים של Ionic Digital

トニー・ヴェイセリ、フィギュア・マーケッツ、GXDラボが説明を行い、アイオニック・デジタルの取締役会と会談

Tony Vejseli, Figure Markets en GXD Labs geven verduidelijking, ontmoeten de raad van bestuur van Ionic Digital

Tony Vejseli, Figure Markets și GXD Labs oferă clarificări, s-au întâlnit cu Consiliul Ionic Digital

Tony Vejseli, Figure Markets Uye GXD Labs Inopa Kujekeswa, Yakasangana neIonic Digital's Board.

Тони Вејсели, Маркет Маркетс и ГКСД Лабс пружају појашњење, састао се са одбором Иониц Дигитал-а

Tony Vejseli, Masoko ya Kielelezo na Maabara ya GXD Hutoa Ufafanuzi, Alikutana na Bodi ya Ionic Digital.

Тони Вейсели, бозорҳои фигурӣ ва лабораторияҳои GXD тавзеҳот медиҳанд, ки бо Шӯрои Ionic Digital мулоқот карданд

If you have been avoiding mobile test automation because it sounds too complex or you are unsure where to start, fear not! When it comes to end-to-end testing for mobile apps, it can feel a lot like preparing for a trek through an unknown jungle. Whether you are looking to test an Android app or an iOS app, this guide will simplify the setup process and get you kicking with mobile app test automation. Without wasting much time, let’s dive into it. What is Appium? Appium is an open-source, free automation testing tool for mobile. It supports cross-platform testing, meaning it can test native apps and hybrid apps. Pre-requisite Before you begin, ensure you have met the following requirements: Download and Install the latest version of nodejs from the official site here
Download and Install Java Development Kit (JDK) from the official site here
XCode Installed
Android Studio Installed N/B: To verify you have installed node, in your terminal, write node -v which will tell you the current version installed. Installing Appium Open your terminal, and write this command npm install -g appium@2.11.4 to install Appium.
In your terminal write this command appium driver install uiautomator@3.7.2 to install the UI Automator driver.
In your terminal write this command appium driver install xcuitest@7.26.4 to install the XCUITest driver.
In your terminal write this command appium plugin install --source=npm appium-wait-plugin@2.0.3 to install a wait plugin.
Download, and install Appium Inspector from here. That’s it! You are good to go. To run Appium, simply write appium in your terminal, and the server loads up. Getting Started Now that we have installed Appium, we can now write test scripts to test mobile apps. But before we can write any code, we need an IDE. An IDE is a code editor that allows us to write scripts to test and build software. There are many IDEs out there, but for a quick start, we will be using IntelliJ IDE. You can download and install IntelliJ IDE here. You can make use of the community version. Once you have downloaded and installed IntelliJ IDE, open the software. Create a New Project on IntelliJ Click on new project.


Ensure that “Java” is selected as shown below.


Give the project a name.


Select the build as Maven.


Select the JDK installed or registered when you click the drop-down.


Once you are done, click on the Create button. You will be provided with a pom.xml file. Now, the pom.xml file is going to contain the necessary dependencies we need to use to run Appium. Open the pom.xml file, and add the following dependencies: <dependencies>
    <dependency>
        <groupId>io.cucumber</groupId>
        <artifactId>cucumber-java</artifactId>
        <version>7.13.0</version>
        <scope>test</scope>
    </dependency>

    <dependency>
            <groupId>org.testng</groupId>
            <artifactId>testng</artifactId>
            <version>7.9.0</version>
            <scope>test</scope>
        </dependency>

    <dependency>
        <groupId>io.appium</groupId>
        <artifactId>java-client</artifactId>
        <version>8.6.0</version>
    </dependency>

    <dependency>
        <groupId>org.seleniumhq.selenium</groupId>
        <artifactId>selenium-remote-driver</artifactId>
        <version>4.24.0</version>
    </dependency>
</dependencies> Once you add the dependencies above in the pom.xml file, an “m” button may pop up by the top right corner, click on it so that it installs the dependencies. Conclusion So far, we have installed Appium with the related drivers and plugins we need to be able to successfully run Appium on our machine. We have also installed a code editor - IntelliJ. Finally, we have been able to create a new project on add dependencies in the pom.xml file. If you have been avoiding mobile test automation because it sounds too complex or you are unsure where to start, fear not! When it comes to end-to-end testing for mobile apps, it can feel a lot like preparing for a trek through an unknown jungle. Whether you are looking to test an Android app or an iOS app, this guide will simplify the setup process and get you kicking with mobile app test automation. Without wasting much time, let’s dive into it. What is Appium? Appium is an open-source, free automation testing tool for mobile. It supports cross-platform testing, meaning it can test native apps and hybrid apps. Pre-requisite Before you begin, ensure you have met the following requirements: Download and Install the latest version of nodejs from the official site here Download and Install Java Development Kit (JDK) from the official site here XCode Installed Android Studio Installed Download and Install the latest version of nodejs from the official site here here Download and Install Java Development Kit (JDK) from the official site here here XCode Installed Android Studio Installed N/B: To verify you have installed node, in your terminal, write node -v which will tell you the current version installed. N/B: To verify you have installed node, in your terminal, write node -v which will tell you the current version installed. Installing Appium Open your terminal, and write this command npm install -g appium@2.11.4 to install Appium. In your terminal write this command appium driver install uiautomator@3.7.2 to install the UI Automator driver. In your terminal write this command appium driver install xcuitest@7.26.4 to install the XCUITest driver. In your terminal write this command appium plugin install --source=npm appium-wait-plugin@2.0.3 to install a wait plugin. Download, and install Appium Inspector from here. Open your terminal, and write this command npm install -g appium@2.11.4 to install Appium. npm install -g appium@2.11.4 In your terminal write this command appium driver install uiautomator@3.7.2 to install the UI Automator driver. appium driver install uiautomator@3.7.2 In your terminal write this command appium driver install xcuitest@7.26.4 to install the XCUITest driver. appium driver install xcuitest@7.26.4 In your terminal write this command appium plugin install --source=npm appium-wait-plugin@2.0.3 to install a wait plugin. appium plugin install --source=npm appium-wait-plugin@2.0.3 Download, and install Appium Inspector from here . here That’s it! You are good to go. To run Appium, simply write appium in your terminal, and the server loads up. appium Getting Started Now that we have installed Appium, we can now write test scripts to test mobile apps. But before we can write any code, we need an IDE. An IDE is a code editor that allows us to write scripts to test and build software. There are many IDEs out there, but for a quick start, we will be using IntelliJ IDE. You can download and install IntelliJ IDE here . You can make use of the community version. here Once you have downloaded and installed IntelliJ IDE, open the software. Create a New Project on IntelliJ Click on new project. Ensure that “Java” is selected as shown below. Give the project a name. Select the build as Maven. Select the JDK installed or registered when you click the drop-down. Once you are done, click on the Create button. Click on new project. Click on new project. Ensure that “Java” is selected as shown below. Ensure that “Java” is selected as shown below. Give the project a name. Give the project a name. Select the build as Maven. Select the build as Maven. Select the JDK installed or registered when you click the drop-down. Select the JDK installed or registered when you click the drop-down. Once you are done, click on the Create button. Once you are done, click on the Create button. You will be provided with a pom.xml file. Now, the pom.xml file is going to contain the necessary dependencies we need to use to run Appium. Open the pom.xml file, and add the following dependencies: <dependencies>
    <dependency>
        <groupId>io.cucumber</groupId>
        <artifactId>cucumber-java</artifactId>
        <version>7.13.0</version>
        <scope>test</scope>
    </dependency>

    <dependency>
            <groupId>org.testng</groupId>
            <artifactId>testng</artifactId>
            <version>7.9.0</version>
            <scope>test</scope>
        </dependency>

    <dependency>
        <groupId>io.appium</groupId>
        <artifactId>java-client</artifactId>
        <version>8.6.0</version>
    </dependency>

    <dependency>
        <groupId>org.seleniumhq.selenium</groupId>
        <artifactId>selenium-remote-driver</artifactId>
        <version>4.24.0</version>
    </dependency>
</dependencies> <dependencies>
    <dependency>
        <groupId>io.cucumber</groupId>
        <artifactId>cucumber-java</artifactId>
        <version>7.13.0</version>
        <scope>test</scope>
    </dependency>

    <dependency>
            <groupId>org.testng</groupId>
            <artifactId>testng</artifactId>
            <version>7.9.0</version>
            <scope>test</scope>
        </dependency>

    <dependency>
        <groupId>io.appium</groupId>
        <artifactId>java-client</artifactId>
        <version>8.6.0</version>
    </dependency>

    <dependency>
        <groupId>org.seleniumhq.selenium</groupId>
        <artifactId>selenium-remote-driver</artifactId>
        <version>4.24.0</version>
    </dependency>
</dependencies> Once you add the dependencies above in the pom.xml file, an “m” button may pop up by the top right corner, click on it so that it installs the dependencies. Conclusion So far, we have installed Appium with the related drivers and plugins we need to be able to successfully run Appium on our machine. We have also installed a code editor - IntelliJ. Finally, we have been able to create a new project on add dependencies in the pom.xml file.

Mobile App Test Automation - Getting Started With Appium Part 1

Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk. Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering. Traditionally speaking, the banking system works with the help of a vast network of reliable intermediaries. Despite its challenges and shortcomings, we continue to rely on it to protect our funds and valuables – primarily in the virtual safe deposit box. This trust has been built over the centuries by the traditional banking system. Meanwhile, in the non-traditional landscape of cryptocurrency, the idea of a self-custody wallet has continued to gain traction even though bad actors are constantly in the news for hacking exchanges. While the crypto industry has undergone significant development, it is still very much plagued by scams and hacks that undermine efforts to build trust among millions of potential users. Crypto has an image problem, despite the promises of a self-custody revolution, and this is only aggravated by the instances of “overnight millionaires”. As a technological innovation, self-custody, which moves the management of assets into the hands of customers, represents a paradigm shift. It eliminates third-party involvement—a feature that can be a lifesaver as many platforms such as Terra, Celsius, and FTX, to mention a few, have crumbled causing significant losses to the tune of $40 billion as per CoinDesk . Crypto CoinDesk Building Trust Over Time It has taken several years of legal framing and enhancing the security measures of the conventional banking systems for people to develop trust in those systems. For instance when Silicon Valley Bank went bust, requisite measures to deal with customer losses were instituted without any delay. Silicon Valley Bank Crypto business, conversely, is a rather ill-defined and continuously developing market that still has no set rules to follow. Trust in this space has often been lost due to several failures as well as fraud-related cases. Consequently, self-custody appears to be the most viable innovation in such an environment. We can own assets outright and decrease the risk associated with third parties, which makes the process free from their intervention. The Role of Technology in Enhancing Security In the future, as this industry develops, we should also see these self-custody technologies reach the same high levels of trust and reliability as the present-day banking sector. Currently, CCData reveals that over one hundred providers can be identified all over the world to provide custodial solutions to retail and institutional investors looking to invest in crypto assets. The consolidation of the industry is foreseeable, as it is borne out by the experiences of sectors such as banking and the internet when transitions are initiated to tighten up security and instill greater trust in the industry. Distrust of centralized infrastructure is another problem that might appear unfathomable for retail users, but self-custody is imperative. The self-custody market remains to be developing, providing better and more consumer-friendly solutions that handle assets on the user‘s behalf. Additionally, self-custody is not only about transitioning between one technological paradigm and another – but a paradigm shift in thought. That is an indication of a shift towards self-organization and one’s faith in the financial systems. Unfortunately, self-custody will become one of the standards as crypto develops further for those who want their funds to be secure. Challenges Facing Web3 Wallet Management Currently, managing a Web3 wallet comes with the following challenges: Seed Phrases A Web3 wallet most importantly comprises the seed phrase recognized as a recovery phrase. It serves the purpose of becoming a unique identifier, allowing users to restore their wallets on various gadgets. It is a 12-24 random word phrase, and losing such a phrase will result in permanent loss of wallet and any of the funds stored in it. Unfortunately, there is no organized service to recover the phrase, and the total burden lies on the user. The problem lies in the question of how to safely store this seed phrase securely at the same time. It is too long and random that users cannot memorize it easily, and when they write it down or store it in an informatics device, there are some dangers involved. If the physical copy is lost, damaged, or stolen — or if a digital copy of the information is cracked — the user’s wallet could leak or could be locked away forever. Generating and Remembering Strong Passwords The majority of Web3 wallets also force users to set essential passwords to enhance the application’s protection. Such passwords must be used so that one is long and different from those used in the other accounts and contains symbols that cannot be subjected to hacking or brute force. However, this creates a significant challenge: how to achieve the best password creation to meet the standard of secularity while, at the same time be okay with the user to remember it. The reality is that there is no one server that a person can turn to get help, and as such, if the password is gone, so is the wallet. Worse still, fundamental password reset strategies such as receiving password reset links via email are not feasible in Web 3. As a result, the wallet remains closed for all eternity if the user forgets or loses the password to the wallet. This password is only with the user, so password insecurity is still an issue when managing Web3 wallets. Protecting Against Phishing Scams and Malware Crypto phishing scams are one of the most common types of scams actively used in the Web3 ecosystem. The attackers continue hiding behind the replica of any type of service or person, using techniques ranging from private keys to passwords from the user. As pointed out it has been noted that this kind of scam has evolved in a way that when the individual clicks on the links to the sites involved, these look almost like the real site, putting even the intelligent users at the mercy of the con-men. Malware is another huge problem because it is easy to spread an infected file or program into an organization's network. This can be acquired through downloads or by clicking on links in ads and will surreptitiously steal wallet details. For example, some malware may keep track of the clipboard of the user to replace the copied wallet address with a fake one, so as to guarantee that users deposit their cash into the wrong wallet. That is why pointing interest from the user and awareness of threats in the information space is needed to prevent these forms of attacks. Remaining Cautious of Unknown Links and Downloads Among the most used attack methods in Web3 is using links or downloads, which sound familiar or unknown to the user. If the user clicks on a fraudulent link, then the wallet becomes vulnerable to phishing sites, or the user's device is infected with malware. These are attacks with the intent of capturing the private key or otherwise phishing users into signing up for fraudulent transactions. Given the fact that Web3 is a decentralized network system, there is effectively no protection, and users are their self-defense line. This challenge is especially challenging because links can be disguised in several different ways, shapes, and forms. It comes from emails pretending to be from customer support or alert services on social media sites. One can compromise their account easily simply by downloading a well-known wallet plugin from untrusted sources. It makes every exchange that occurs through the platforms a potential risk that needs to be avoided. How GRVT Is Challenging The Notion of Private Key How GRVT Is Challenging The Notion of Private Key The GRVT Wallet simplifies the user experience through Web Authentication (WebAuthn), which allows users to create and access their wallet using a password and passkeys, avoiding the complexities associated with traditional crypto wallets. The integration of Dfns technology allows users to access their wallets via fingerprint or facial recognition, offering quick and secure authentication similar to traditional online banking. And it blends the user-friendliness of Web2 with the security of self-custody, protecting assets without the technical burdens. By leveraging off-chain, peer-to-peer networks with multi-party computation (MPC) and public key infrastructure, it is able to guarantee: No Single Point of Failure: GRVT Wallet supports multiple devices, creating multiple security layers to prevent breaches. Responsive Recovery: Recovery wallets and backup codes provide fail-safes if credentials are lost. Uninterrupted Transactions: Linking new devices doesn’t affect public key, allowing continuous transfers. Conclusion The question of why the conventional banking system continues to thrive despite its shortcomings and the revolutionary advantage of the self-custody system boils down to trust. Millions around the world still feel safe to keep their money and other valuables in the banks and the incidence of crypto scams and losses has increasingly overshadowed the prospects of a generational transition from modern banking to cryptocurrency and self-custody wallet. This problem is further aggravated by the technical complexities surrounding the use of a smart contract wallet, which requires a level of skill to operate. Nonetheless, the possibility for both systems to exist side-by-side in the future is worth considering.

The Vaults vs. Self-Custody: A Trust Revolution in Modern Finance

The Vaults vs Self-Custody: A Trust Revolution in Modern Finance

Сховішчы супраць самастойнай апекі: рэвалюцыя даверу ў сучасных фінансах

Трезорите срещу самопопечителство: Революция на доверието в съвременните финанси

Las bóvedas frente a la autocustodia: una revolución de la confianza en las finanzas modernas

Brankas vs. Penitipan Diri: Revolusi Kepercayaan dalam Keuangan Modern

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