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INTEVITY ACQUIRES TECHABO

The private equity arm of an NYC firm has acquired a majority stake in Columbus-based Sage Sustainable Electronics, accelerating its mission to keep old corporate laptops, phones and other devices out of landfills.

Columbus e-waste company sells majority stake to keep more laptops out of landfills

In its ninth year, the Transform Awards North America celebrates excellence in brand development, rebranding and reputation management. The collaboration between Unisys and Landor & Fitch resulted in a multi-dimensional creative reimagining that modernized the 150-year-old IT brand for the first time since 1986.

Unisys Brand Transformation Work Shines with Three Gold Awards at Transform Awards North America 2023

Intuitive (Nasdaq:ISRG) announced that it appointed Align Technology executive Sreelakshmi Kolli to its board of directors.

Intuitive appoints Align Technology exec to its board

Through her nonprofit workforce development organization, Gateway Global, Zekita Armstrong Asuquo is preparing under-resourced high school students for entry-level jobs in the geospatial field.

Mapping tomorrow: St. Louis nonprofit trains next generation of geospatial industry workers

Whitten announced funding for two new research institutes: the Convergent Bioscience and Technology Institute and the Institute for Human Health and Wellbeing. These investments will total more than $250 million. Read more: IU invests $111 million in microelectronics for workforce, research and national security

Whitten to invest $250 million in life and health sciences

Wisconsin won its tech hub bid with a Milwaukee-Madison consortium focused on biohealth and personalized medicine. It was selected from a pool of more than 370 applicants across 49 states. These are just some of the places that submitted tech hub proposals and weren't selected as designated hubs.

Wisconsin won a coveted tech hub designation. See which places it beat out.

CMG Home Loans in Hawaii is now offering a crowd-funding platform that aims to help homebuyers raise money for their down payments.

New platform helps homebuyers raise money for down payments

Japanese automaker Isuzu has unveiled its first electric bus, the Isuzu Erga EV. The Erga EV is being touted as the world’s first battery electric flat-floor bus. It was on display during the 2023 Japan Mobility Show and is scheduled to enter the Japanese market in 2024.

Isuzu unveils the Erga EV bus as the world’s first battery-electric flat-floor route bus

Mouser Electronics Partners with Siemens on Distribution Agreement for Industrial Automation Solutions

Intuz

intuz

Top 30 Cloud Consulting Companies to Take Notice of in 2020

The tech world is one of the most dynamic segments in the whole universe. One moment, the world is behind a technology and the next moment, suddenly, the technology becomes obsolete. Similar is the case with the app world, too. Numerous tech stacks, frameworks, and languages are available to develop an app but still, developers are not confident about a single framework that can offer the best results. As the world is adjusting to conventional apps, the whole ecosystem is also evolving. dApps or decentralized applications are a novel breed of applications that are not controlled or owned by a single authority, cannot be shut-off or cannot have a downtime. dApps: The Ultimate Open Source Revolution The dApp concept is still in its nascent stage. Explaining the same in a single line is tough because no specific definition seems to fit all the attributes that make an application a decentralized app. As dApps, an application is required to exhibit the following four characteristics: The first and foremost attribute is that such apps should make their core source code available to everyone. As the core characteristic of dApps is autonomy and unanimous consensus, essentially the changes must be decided by all or the majority of the users. Also, the code should be available to everyone for checking out. Open Source: As the name suggests, decentralized applications stores everything on a decentralized blockchain or any cryptographic technology to save the app from perils of centralized authority and emphasize on autonomous nature. Decentralized Nature: As the app is based on the decentralized blockchain, the validators of the records on the network must be rewarded/incentivized with cryptographic tokens or any form of digital asset that has value. Incentivization: Decentralized app needs to have a consensus mechanism that portrays proof of value in the cryptographic system. Essentially, this endows value to the cryptographic token and creates a consensus protocol that users agree upon to generate valuable crypto tokens. Algorithm: Now that we know the characteristics, we can try to fit it into a definition that will help us identify real-life examples. Essentially, dApp is an application that runs on decentralized P2P network governed by all the members and not a single central authority. How dApps fit in the real world? Utilizing the definition derived above, we found out that the first known dApp in the world was the Bitcoin. Popular as an apex cryptocurrency, bitcoin solves the centralization issue and gives users the power to perform transactions without any middleman or central authority via a self-sustaining public ledger. Coming to the use case of decentralized applications, we can classify these apps based on the scenario they can be infused into. This classification categorizes dApps into three segments that are also its potential use cases: Money Management & Transfer Decentralized apps can be used to smoothen money transfer in the world. We have already seen the benefits in the form of success of bitcoin and other cryptocurrencies. Using blockchain network and its own crypto token, dApps can speed up money management, transfer, and lending by eliminating middlemen and enhance security due to the consensus mechanism that is impossible to change without a majority. Business Process Management Companies can integrate decentralized applications to streamline processes without human intervention. With the help of smart contracts- an essential cog in the blockchain network, critical issues can be solved and process efficiency can be enhanced. For example, logistics companies can integrate RFID chips into their shipment that can be scanned at the destination ports on which the payment can be settled automatically through a smart contract between buyer and seller. DAO (Decentralized Autonomous Organization) DAO is a completely new phenomenon of starting faceless organizations without leaders. These organizations can work as a corporate and run via rules that are defined by programming languages on the blockchain. How members will vote, what business segment will the organization operate in, who can be members, how will the value token be exchanged, everything can be programmed on the blockchain that will run the organization. These organization cannot stop once deployed and can work worldwide, without any trouble riding on the blockchain network bandwagon. Real-world dApp examples: Successful dApps Projects in the world Most dApps are focused on money management and simplifying money transfer. Most of the cryptocurrencies remove the friction associated with P2P transfers. But, there are some innovative use cases of dApps, too. For instance, Factom is an open-source record keeping system that is unalterable. There are some other promising dApps projects that are transforming the app landscape. These include: Golem Golem utilizes idle computer power and its first use case came out in the form of Brass Golem. Brass Golem aims at improving CGI rendering landscape by giving CGI artists the power to rent out powerful computing resource as per the CGI requirement. By creating a decentralized network, idle machines are put to a good use by giving them the power to accept tasks from the users of Golem network. This is the next level of resource sharing and pooling that is being made possible by Goem dApp. Augur Augur aims at blending the power of decentralized network with prediction algorithms to create full-proof forecasting tools for markets. Though the app is still under beta testing, the potential implications are quite promising. The app will be able to input real-world events into other events to create an unalterable blockchain network of true facts that can be used for reference across industries. Status Status runs a peer-to-peer network where users can send payments to each other and enter into a smart contract. Via the messenger system, users can stay connected without the problem of server downtime as everything is based on blockchain P2P network. Developing dApps: How to build a powerful decentralized app? Just like any new programming concept or technology, there is a wide range of coding options and platforms that developers can leverage while thinking of developing decentralized applications. If you have to develop a dApp for yourself, you need to get hold of proper tools, components, and frameworks for success. We have tried to compare dApp development with conventional development and compile everything you need to build a decentralized app in the following table: dApps are based on backend code operating on a P2P network. When compared to conventional apps, this is a major difference as a normal app’s backend runs on a centralized server. When it comes to the frontend, the code can be written in any programming language. Using an API, frontend calls the backend in case of decentralized applications. Also, frontend can also be hosted on a decentralized storage system such as IPFS. Now you see how different development of a decentralized app is compared to a normal app, let’s focus on the benefits of choosing dApps over apps managed via centralized servers. Why choose dApp development over conventional app development? dApps promotes decentralization making them tamperproof and the records unalterable. As dApps are based on a secure blockchain network, such apps promote a high level of security and are immutable from hacks and intrusions. Faster & payment processing without needing to integrate payment gateway to accept funds. High levels of data security due to smart contracts governed by private keys. Greater anonymity without needing the users to follow the lengthy signup process. Reliable data records as users can access the public blockchain to verify transaction information. For kickstarting a successful dApps project, you need an who has the agility and expertise to handle complex frameworks. In order to, make your decentralised app development journey successful, you need a dependable companion with experience of deploying successful dApps. Intuz has been working in the dApps domain for quite a while and offers specialised blockchain services for several industries. Engage with Intuz dApps experts and . expert blockchain developer contact us now Read My Previous Articles on Blockchain/Cryptocurrency How to Build a Cryptocurrency Exchange App How To Launch And Market Your Own Cryptocurrency/ICO Stay tuned with us on , , and for other interesting news from us! Also: Twitter Facebook LinkedIn

What Are Decentralized Applications (dApps)? — Explained With Examples

Top Web Development Companies in 2018

2017 gave exciting glimpses of what mobile and industry is doing in the field of Internet of Thing (IoT) and sixth sense technologies. Smartwatch, fitness tracker bands and smart household appliances have flooded the markets over the past year and smartphone operating system and device manufacturers have taken up the task of supporting these technologies with gusto. Demand for applications to support IoT technologies has risen and the focus towards their development has received impetus. We take a look at the top 10 IoT app companies of 2018 - software development 1. Intuz Intuz works with clients worldwide for developing mobile and web applications of very advanced features. It was a natural progression for this company to adopt the latest development standards and deliver advanced IoT enabled features in the mobile applications developed by them. They have used IoT features such as GPS, Beacon and sensors to deliver applications for various commercial application in petrol station, Hotel Booking Startup and for a Marketing Platform provider. 2. Softeq Softeq specializes in developing custom apps for mobile and web platforms and wearable devices. Their engineers have both hardware-level and application level expertise, which they merge to deliver highly functional applications. They have so far delivered apps for wearables, augmented reality games, SmartTV, IPTV & VoD solutions. 3. AppInventiv AppInventiv is a top-ranked web and mobile development company which is most sought for working on emerging destructive technologies. They specialize in IoT, wearable and augmented reality technology based app development. Their notable work on IoT apps include a Hearing Aid Non Profit application for those with hearing disability that uses GPS capabilities. They have also designed apps for companies from entertainment industry, primarily focusing on UI/UX design. 4. Solution Analysts Solution Analysts forayed into IoT-based mobile application design and development with the onset of iBeacon and growth in wearable device in the market. They have used GPS and beacon technology extensively to develop commercial applications for retail stores and event management industry. They have also developed notable applications for the iWatch. 5. Octal Info Solutions Octal Info Solutions have their business interests spread across development for web and mobile platform, and with the increasing focus on IoT, big data and cloud solutions, they are building their profile in this segment too. Some of their work using IoT technologies are for an international packers and movers company that assists in international relocation by giving users services such as providing information city guides. It has also worked with a retail shop to increase the footfall of shoppers by designing a mobile application. 6. Menlo Technologies Menlo Technologies is one of the leading software solutions developer with a global presence and a large team of software developers and engineers. They deliver strategic IT solutions to clients that enable them to leverage technology to meet their business goals. They are using IoT technologies for mobile application development in fields as diverse as working with a semiconductor company to develop tools, to working with a data services company as their technical resource provider. 7. FS Studio FS Studio is an advanced software consulting firm that specializes in providing support with embedded device products and virtual reality. They work largely on machine learning and computer vision. They have worked extensively in children’s technology market and created entire solutions from foundation for company’s technology initiative. Some of their notable work has been in developing custom solutions for a boutique marketing agency and created augmented reality enabled gaming applications for a children’s toy company. 8. Swenson He Swenson He works with business to provide end-to-end software solutions development, adhering to their most complex needs with their group of highly proficient engineers. They are currently working with the latest IoT technologies to enable companies manufacturing smart products to augment their products efficiency and usability. They are recommended by clients for the smart UI design, which makes interaction of the smart product with the smart app a child’s play. 9. HQSoftware HQSoftware is known for its high level of involvement with the client project, engaging clients at various levels to accomplish the project within stipulated time and limiting costs. They are providing feasible IoT-based solutions to companies that want to move to the new standard without escalating their costs. Some of their work engages a textile factory, IT firm and a digital agency, enabling them to design engaging solutions. 10. Lemberg Solutions Lemberg Solution provides web, mobile and IoT development solutions and currently has experience working with travel and hospitality, automotive, healthcare, social networking and consumer electronics industries. In IoT development, they do hardware design and prototyping and firmware development. They have designed learning applications for an eLearning firm and a College mobile app and an AR Freeflight app that uses the drone technology. The above list has been condensed from a list of IoT development company, picking the top ranking mobile app development companies, by selecting them for their highest scores in the area of IoT development.

Top 10 IoT (Internet of Things) App Development Companies | IoT Solutions Leader 2018

A sophisticated way of customer management service, an invaluable asset for small companies and an awesome tool to derive business intelligence — we are talking about Chatbots. Chatbots, if leveraged in the true and accurate sense can deliver ultimate customer satisfaction and streamline the support functions for small organizations. One has witnessed a meteoric rise in chatbots over the past few years. Chatbots have become all –pervasive — so where you are ordering food (Zomato), calling a cab (eg. UBER) or booking a movie ticket you could have all your conversations with a chatbot residing in the app/website of your choice. What is a Chatbot? Computer programs that can converse to the users like real human are called chatbots. Almost all prominent messaging apps are making use of chatbots. Companies both big/small give an identity to their chatbots and these bots are designed smartly to understand spoken and written text. The bots then decipher the meaning and offer the aptest information/solution to the users. Technologies used in Chatbot Chatbots function on two types of technology: AI based chatbots Command based chatbots AI-based Chatbots are based on natural language processing and thus can answer vague and ambiguous questions too. AI-based chatbots generate answers by making use of the natural language process and improvise themselves from the learnings of the past questions. Command based chatbots work on hard-coded messages, heuristics, and databank of questions and answers. Command chatbots cannot generate text themselves. However, the bot is intelligent to understand the question of the user and select a reply that corresponds to the query asked. Command Chatbots are more dependable and grammatically correct. However, they cannot offer answers to questions that are outside their preview. Features of command based chatbots: Command based chatbots can have only a limited set of questions and answers. Answers can only be sought for questions that are fed in the chatbot. Manual intervention is needed for uncommon questions (questions that are not in the repository) Chatbots are the first line of customer support, they feature a conversational UI and many of them require no coding too. They are must for small businesses that are looking to create customer delight and in turn, earn loyal customers for their business. Reasons why small businesses need a chatbot An interactive marketing platform Chatbots create an active user experience, unlike apps and websites. And thus can be used for an interactive marketing campaign. Chatbots can help a small business reach out to more audience without extra cost. Chatbots on Facebook Messenger is an example of how companies can reach out to more people effectively and at a lower cost. 24/7 Availability As a small business, you would not need to invest in employing additional resources for your business to engage with your customers or stakeholders. The productive hours or an employee is 5/6 hours. However, the Chatbot can run efficiently 24X7. Thus, no additional shift means no additional cost. Quick support for customers Chatbots act as instant support for customers. All important and most asked questions can instantly be answered via chatbots, without customers having to wait on the phone call and undergo the maddening on-hold music. Chatbots also allow small businesses to control & set the tone of the call and ensure brand consistency. Scales up business operations Chatbots help small business scale up their operations as they do not have limitations related to time & efficiency. Unlike human agents who can handle only 2 to 3 calls at a time, Chatbots, when used to complement your task force, can offer quick solutions to more customers. Decreases Customer Acquisition Cost One of the main challenges for small businesses is lowering Customer Acquisition Cost. Chatbot can be of great help here too. Chatbots can be designed to handle sales. A salesperson can handle only a defined number of customer requests, but a Chatbot can process gigabytes of data at one go. This would lead to quicker response and happier customers. Helps to Earn More Revenue with Better Engagement Chatbots can be customized to upsell/cross-sell. Small businesses can stay ahead of competition by making use of Chatbots instead of employing a large sale force. This would help cut down on costs. Businesses that have similar products can also use Chatbots to sell related product. Chatbots can offer the right advice to customers and help them buy related products and the right and meaningful benefits can be pitched through Chatbots. For instance, a lense can be pitched to a person who is buying a camera. Chatbots can explain and convince users to buy expensive products by explaining the benefits & values of a product/service. Increases organizational efficiency Small business can lower down their costs significantly by making use of Chatbots instead of a large number of resources for their backend support. Instead of recruiting people for routine and humdrum tasks, using Chatbots would be a better and cost-effective option. Increases Return on Investment (ROI) Customer Retention directly influences yours ROI. According to a reduction of 5 percent in the customer churn rate, increases profit margin between 25 and 125 percent. (source:InsightSquared) InsightSquared Small businesses can make use of AL enabled Chatbots. All they have to do is equip it with the desired knowledge and make it capable to handle all customer queries. The higher customer retention, the more will be the revenue for the business. Increases Customer Satisfaction Customer satisfaction is a key ingredient for the success of small businesses. If the customers are delighted, their tendency to come back increases. With a good, loyal customer base the sales would tend to shoot up. Also, happy customers are more likely to recommend you to their friends and family. Chabots offer quick help and solutions to customers and gain their trust and delight. Reduces Cost Chatbots are less expensive than apps. Chabots can be developed at a much lower cost as compared to the whole application. All small businesses have to keep in mind is that Chabots should be developed in such a way that it offers a great experience to the users. Creates Brand Recall Chatbots can be programmed to be humorous and funny. As a business you can code a small script that has jokes or witty replies to questions. Such Chatbots attract customers and help small businesses create and identity for their business. Thus, Chatbots are one of the most effective ways to add a character/personality to your brand. The benefits of Chatbots are enormous for both big and small businesses. However, certain points need to be kept in mind while developing a Chatbot for your business. What needs to be kept in mind? Chatbots are all about personalization. So, the introductory screen should speak about all the features of the Chatbot. The user should feel welcomed and important. Thus can be achieved by using the name of the user and also with the help of interactions. Make sure that the design of the Chatbot is user-friendly and easy to navigate. Make use of high-resolution pictures and proper text formatting in your Chatbot. Make your Chatbot smart. Ask minimal info from the user and do not repeat the questions. Make sure proper answers are provided with little input from the user’s end. Some Handy Chatbot platforms: — It is an easy to use Chatbot platform that allows users to develop automated bots. FlowXO — It helps you create your Chatbot in just three easy steps. This platform makes use of natural language processing. As a result, the conversational tone of the bot is quite realistic. Morph.ai — This platform needs coding experience. It is mostly used by the developer community to create Chatbots. The interface is however quite simple and easy to comprehend. Chatfuel It is time for small businesses to automate their customer experience for better productivity and Return on Investment (ROI). Right from handling customer queries to streamlining sales/marketing operations, small business can leverage Machine learning and AI Chatbots to grow their business. Are you a small business and looking for interactive way to streamline your sales & business operations? Intuz has a solution. to help them improve customer engagement. We offer customized and technologically advanced Chatbot solutions for small businesses Contact us for free consultation and Chatbot demo.

Chatbots: An Invaluable Asset for Small Businesses - (Don't Ignore)

Voice-activated virtual assistants and artificial intelligence are transforming the way people interact and use technology in modern homes. As of May 2017, Alexa-enabled devices were sold all over the world. Experts already have predicted that Alexa and other voice assistants will become a industry by 2020 as more than 30% interactions with smart devices will be voice-based in the future. 10+ million $10 billion Source: Statista What does such a transitional scenario mean for your small business? With Alexa Skill marketplace brimming with apps at present, how can you leverage the technology for your business benefit? Alexa is not only disrupting how people use technology at home, the business world is also taking cues to simplify common tasks in offices. You need to rapidly invest in building an Alexa Skill for your business looking at the monumental leap in the number of skills in the marketplace. Empowering your Business through Alexa Skill Amazon’s Alexa is not just a homely assistant. It can help you manage several tasks at your office or business with absolute efficiency. Businesses all over the globe have been demonstrating how efficient smart assistants such as Alexa can be in converting a conventional office to a smart office. Recently, showed how to use Alexa to fetch important business reports through voice using Alexa Skills in their ERP. Financialforce Just like Financialforce, entrepreneurs are checking out the applications of Alexa in their regular workplace environment. While some are using Alexa to add meetings to Google Calendar, post messages and add tasks, others are moving to more sophisticated uses of Alexa in a business environment. Create/update to-do lists & track tasks Alexa can be used to update to do lists using a voice command. Entrepreneurs and professionals can use Alexa to schedule an item on the calendar or create a to-do list that can be easily accessed from the Alexa app on mobile or computer. Using a voice-activated command, you can request Alexa to create a reminder. For example, a small command such as Alexa add 3:00 o’clock meeting with Mr. ABC to the calendar will prompt Alexa to add the same to your calendar and notify you just before the right time. Create & track travel itineraries Alexa can streamline business travel for companies with frequent fliers. Using an Alexa skill, employees and business owners can plan for a business trip, book tickets, get alerts for flight delays and cancellations, Skill customization can be done to include more features such as seat maps, weather updates, driving directions, etc. to have complete control over the travel experience. Smart inventory management Alexa skill can be used to manage inventory intelligently. With the help of voice-activated inventory management system in your business, you can access inventory data easily from anywhere, anytime without having to fiddle with complex software or spreadsheets. With more than 20,000 live Alexa Skills, at present, the possibilities and business applications are endless. But for harnessing the Alexa platform, you need to develop the right Alexa Skill by understanding the platform and following a structured process. Let’s see how you can develop an Alexa skill for your small business. Alexa Skills Processing Architecture Source: SlideShare Developing an Alexa Skill for your Business If you are keen on utilizing Alexa’s full potential, you will be required to develop a skill according to your customized business needs. You can think of automating a process, simplifying a structure or improving access. The key to a great Alexa skill is simplicity and innovation. Once you have identified the core business area that needs voice-assisted support, you will have to follow the below-mentioned steps for creating an Alexa Skill: Design Voice User Interface for Alexa Skill The most important step of creating an Alexa skill is to design an intuitive voice user interface. This is how common users, employees and others will activate Alexa for using the skill. To design a proper interface you will have to create a flowchart that will define the path of user interaction. The flowchart will help you in identifying various types of user requests. The identified user requests will become Intents are actions required to be performed by Alexa to fulfill the user request. intents. Source: Amazon Start creating a skill in the Developer Console With the help of , you can start building your skill. You will be required to define the name of the skill, languages supported and the interaction model for your Alexa skill. Amazon’s developer console As you are building a skill from scratch for your unique business idea, select custom interaction model when prompted. In the custom model you can define the requests your skill can handle and sample utterances that will trigger the skill. Configure Voice Design to Create Your Interaction Model Your interaction model will define how the skill will respond to a user. It basically consists of collection of intents, sample utterances and the dialog mode. As stated earlier, intents are the requests that your skill can handle i.e. basic functionality. Sample utterances are the words and phrases that users will use to express intent. Dialog model will identify the information required to complete a request and the conversation Alexa can use to collect and confirm the same information while interacting with the user. Write the Code for your Skill The basic premise of Alexa skill coding is to complete the task of accepting user requests and send back appropriate responses. To start coding, you can use AWS Lambda to run the code without having to manage servers. Use Node.js, Java, Python or C# to write down the basic code if you are thinking to use AWS Lambda. If you want to host your skill as a web service, you can even use other programming languages. The code should be capable of handling user requests, implement built-in intents, understand account linking, access Alexa shopping and to-do lists to perform the desired task. After you are done with coding, test your skill on the Alexa Test page or using an Alexa-enabled device. Don’t forget to update endpoint of your skill in the developer’s console before moving forward with testing. Once you are done with testing, add metadata about your skill that would show up in Alexa Skills Store. Conduct a Beta Test Once everything is complete, you can invite beta testers to check out and test your skill before the actual launch. You can select beta testers or can invite anyone from the general public. Beta testing is completely optional but will enable you to gather feedback that will help you in improving your Alexa skill. Submit your Alexa Skill for certification After you have completed the process and are ready to roll out your Alexa skill for users, you should submit it for certification. Even if your beta testing is not complete you can submit your skill. Before submitting, you should run all the functional and validation tests listed on the Certification page in the developer console. Make sure that you comply with the submission checklist to speed up the process of certification. After you are confident enough about your Alexa skill, submit the same to Amazon for certification. After Amazon approves your skill, users can view, enable and use the skill to complete the tasks. Next Step Creating an Alexa Skill for business can streamline common tasks and even improve overall efficiency inside your organization. If you are finding the process of developing a custom Alexa skill confusing, you can always . We at are continuously disrupting the voice-based search ecosystem with reliable Alexa Skill development services. Our experts can create reliable Alexa Skills that you can put to use in your business for better operations and employee engagement. take help of specialist Alexa skill developers Intuz

How to Create an Alexa Skill For Your Small Business?

"In today's digital age, security compliance is not just a necessity but a cornerstone of trust," says Akshay Sekar Chandrasekaran, a leading compliance engineering expert at Intuit. He provides insights at a crucial time when cybersecurity threats and regulatory complexities are at an all-time high. Akshay directly enhances Intuit's security environment with his initiatives, setting a high bar for digital security across the industry. The Imperative of Compliance in a Digital World Immense pressure forces businesses to fortify their defenses while adhering to increasingly stringent regulatory requirements. Intuit, a global financial software company, faces these challenges head-on and uses professionals like Akshay Sekar Chandrasekaran to enhance its security posture. Akshay integrates advanced automation and machine learning into compliance engineering, streamlining processes and reducing human error with his innovative methodologies. "We’ve reinforced a system that automates compliance checks across many layers, significantly reducing the risk of non-compliance and potential breaches," Akshay explains. "This has been a game-changer for us, allowing for continuous monitoring and swift responses to potential threats." Intuit Assist: A Revolution in Financial Guidance Intuit Assist, a distinctive artificial intelligence (AI)-a powered platform offering personalized financial guidance to over 100 million subscribers, is central to Intuit's innovative course of action. Akshay’s role in the development of Intuit Assist was crucial via the achievement of compliance certifications along with the development of new security controls, policies, and standards, which paved the way for an advanced assistant. The system handles 810 million AI-driven interactions and 25 million natural language conversations annually. Intuit Assist provides real-time data to offer customized guidance that adapts to each user's unique financial scenario, setting itself apart. Unlike conventional financial tools that basically react to user inputs, Intuit Assist takes a proactive stance, anticipating needs based on a deep understanding of each user's financial journey. By seamlessly integrating across Intuit products such as Quickbooks, TurboTax, Credit Karma, and MailChimp, it democratizes financial decision-making for individuals and businesses. Compliance certifications served as a cornerstone to the integration of the assistant across Intuit products whilst also allowing data sharing between Intuit and its financial partners. "Automation in compliance improves accuracy, but it also enhances our ability to predict and prevent security incidents," says Akshay Sekar. "Foresight is a superpower that only AI can supply for now." Automating Compliance: A Technological Leap Akshay leads the compliance automation framework at Intuit, utilizing automation and artificial intelligence to perform real-time audits and generate comprehensive, easy-to-interpret reports. This innovation has streamlined the auditing process, reducing the time required from weeks to mere hours. This allows Intuit to maintain compliance with global security compliance standards such as ISO 27001, PCI, SOC2, and SOX  more efficiently, freeing up resources to focus on proactive security measures. In 2023, Intuit's automated systems flagged potential vulnerabilities in third-party integrations, allowing immediate mitigation before any exploit could occur. A Vision for Sustainable Security As the digital terrain shapeshifts, strategies employed to secure it must also change. Akshay envisions a future where compliance engineering is fully integrated into enterprise operations and advances with AI and machine learning. This integration will enable security frameworks to be more dynamic and responsive and adapt to new threats in real-time. "The future of compliance engineering lies in its ability to scale with the changing digital environment," Akshay reflects. "Our goal is to create a resilient infrastructure that not only meets today's standards but anticipates and prepares for tomorrow's challenges." Akshay Sekar Chandrasekaran exemplifies the critical role of compliance engineering in modern enterprise security through his work at Intuit. He has bolstered Intuit's defenses and set a new industry benchmark through his use of automation and AI. "Ultimately, our mission is to build trust through security," concludes Akshay Sekar Chandrasekaran. "We can establish a safer digital future for everyone by staying ahead of regulatory demands and emerging threats." This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here. "In today's digital age, security compliance is not just a necessity but a cornerstone of trust," says Akshay Sekar Chandrasekaran, a leading compliance engineering expert at Intuit. He provides insights at a crucial time when cybersecurity threats and regulatory complexities are at an all-time high. "In today's digital age, security compliance is not just a necessity but a cornerstone of trust," Akshay directly enhances Intuit's security environment with his initiatives, setting a high bar for digital security across the industry. The Imperative of Compliance in a Digital World The Imperative of Compliance in a Digital World Immense pressure forces businesses to fortify their defenses while adhering to increasingly stringent regulatory requirements. Intuit, a global financial software company, faces these challenges head-on and uses professionals like Akshay Sekar Chandrasekaran to enhance its security posture. Akshay integrates advanced automation and machine learning into compliance engineering, streamlining processes and reducing human error with his innovative methodologies. "We’ve reinforced a system that automates compliance checks across many layers, significantly reducing the risk of non-compliance and potential breaches," Akshay explains. "This has been a game-changer for us, allowing for continuous monitoring and swift responses to potential threats." "We’ve reinforced a system that automates compliance checks across many layers, significantly reducing the risk of non-compliance and potential breaches," "This has been a game-changer for us, allowing for continuous monitoring and swift responses to potential threats." Intuit Assist: A Revolution in Financial Guidance Intuit Assist: A Revolution in Financial Guidance Intuit Assist, a distinctive artificial intelligence (AI)-a powered platform offering personalized financial guidance to over 100 million subscribers, is central to Intuit's innovative course of action. Akshay’s role in the development of Intuit Assist was crucial via the achievement of compliance certifications along with the development of new security controls, policies, and standards, which paved the way for an advanced assistant . The system handles 810 million AI-driven interactions and 25 million natural language conversations annually. advanced assistant advanced assistant Intuit Assist provides real-time data to offer customized guidance that adapts to each user's unique financial scenario, setting itself apart. Unlike conventional financial tools that basically react to user inputs, Intuit Assist takes a proactive stance, anticipating needs based on a deep understanding of each user's financial journey. By seamlessly integrating across Intuit products such as Quickbooks, TurboTax, Credit Karma, and MailChimp, it democratizes financial decision-making for individuals and businesses. Compliance certifications served as a cornerstone to the integration of the assistant across Intuit products whilst also allowing data sharing between Intuit and its financial partners. "Automation in compliance improves accuracy, but it also enhances our ability to predict and prevent security incidents," says Akshay Sekar. "Foresight is a superpower that only AI can supply for now." "Automation in compliance improves accuracy, but it also enhances our ability to predict and prevent security incidents," "Foresight is a superpower that only AI can supply for now." Automating Compliance: A Technological Leap Automating Compliance: A Technological Leap Akshay leads the compliance automation framework at Intuit, utilizing automation and artificial intelligence to perform real-time audits and generate comprehensive, easy-to-interpret reports. This innovation has streamlined the auditing process, reducing the time required from weeks to mere hours. This allows Intuit to maintain compliance with global security compliance standards such as ISO 27001, PCI, SOC2, and SOX  more efficiently, freeing up resources to focus on proactive security measures. In 2023, Intuit's automated systems flagged potential vulnerabilities in third-party integrations, allowing immediate mitigation before any exploit could occur. A Vision for Sustainable Security A Vision for Sustainable Security As the digital terrain shapeshifts, strategies employed to secure it must also change. Akshay envisions a future where compliance engineering is fully integrated into enterprise operations and advances with AI and machine learning. This integration will enable security frameworks to be more dynamic and responsive and adapt to new threats in real-time. "The future of compliance engineering lies in its ability to scale with the changing digital environment," Akshay reflects. "Our goal is to create a resilient infrastructure that not only meets today's standards but anticipates and prepares for tomorrow's challenges." "The future of compliance engineering lies in its ability to scale with the changing digital environment," "Our goal is to create a resilient infrastructure that not only meets today's standards but anticipates and prepares for tomorrow's challenges." Akshay Sekar Chandrasekaran exemplifies the critical role of compliance engineering in modern enterprise security through his work at Intuit. He has bolstered Intuit's defenses and set a new industry benchmark through his use of automation and AI. "Ultimately, our mission is to build trust through security," concludes Akshay Seka r Chandrasekaran. "We can establish a safer digital future for everyone by staying ahead of regulatory demands and emerging threats." "Ultimately, our mission is to build trust through security," r "We can establish a safer digital future for everyone by staying ahead of regulatory demands and emerging threats." This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here. This piece was published as part of HackerNoon’s Business Blogging Program. For more details, please click here . here here

Compliance Engineering Expert Elevates Enterprise Security at Intuit

কমপ্লায়েন্স ইঞ্জিনিয়ারিং বিশেষজ্ঞ Intuit এ এন্টারপ্রাইজ নিরাপত্তা উন্নত করে

Compliance-Engineering-Experte verbessert Unternehmenssicherheit bei Intuit

Experto en ingeniería de cumplimiento eleva la seguridad empresarial en Intuit

Un expert en ingénierie de conformité élève la sécurité de l'entreprise chez Intuit

अनुपालन इंजीनियरिंग विशेषज्ञ ने इंट्यूट में उद्यम सुरक्षा को उन्नत किया

コンプライアンス エンジニアリングの専門家が Intuit のエンタープライズ セキュリティを向上

규정 준수 엔지니어링 전문가, Intuit의 기업 보안 강화

Especialista em engenharia de conformidade eleva segurança empresarial na Intuit

Эксперт по обеспечению соответствия требованиям повышает безопасность предприятия в Intuit

Uyumluluk Mühendisliği Uzmanı Intuit'te Kurumsal Güvenliği Artırıyor

Chuyên gia kỹ thuật tuân thủ nâng cao bảo mật doanh nghiệp tại Intuit

合规工程专家提升 Intuit 的企业安全性

The Noonification: Leetcode: Two-sum an Intuitive Approach (4/23/2024)

Imagine yourself as the proud owner of a souvenir shop inside the Spot-On Change Hotel. When closing the cash register, you notice an excess of 8 euros. It seems that a guest didn’t receive the exact change. This could tarnish the hotel’s reputation. To avoid this, you decide to solve the mystery of the incorrect change. Upon opening the shop’s cash system, you discover that the error occurred on two different accounts! You devise a plan: to visit each room and ask the guests what change they received in the shop until you find the two with the wrong bill. Arriving on the first floor, a guest reports receiving 4 euros in change. You calculate that you need to find a number that, when added to the 4 euros, results in 8. Moving to the second floor, the guest’s change is 5 euros. 4 + 5 results in 9, so it can’t be this one… Fifth floor, sixth… Tenth, NO, NO, NO! Since you didn’t find the value on the first attempt, you go down to the second floor and start asking all the guests again about their change so that you can compare it with the value from the next starting floor, exhausting, isn’t it? In computer science, this search method is called brute force, an extremely slow search method that works by comparing one item with the following ones in the array. This consumes a lot of time and is not efficient, imagine going up and down all the floors of the Spot-On Change Hotel several times! This is not practical for you and also not practical for the computer. If you’re curious about how this going up and down the floors would be in a software program, it would look like this in JavaScript: twoSum(nums, target) {
  for (let i = 0; i < nums.length; i++) {
    for (let j = i + 1; j < nums.length; j++) {
      if (nums[i] + nums[j] === target) {
        return [i, j];
      }
    }
  }
} After assessing the situation calmly, you realize that there’s a more efficient way to find the two guests with the wrong change. You refine your initial mathematical intuition that 9 euros equals x + y. Applying a bit of arithmetic, you realize that: x + y = 9 is the same as saying that y = 9 — x, and that makes all the difference when increasing the efficiency of your search. Another thing that changed in your strategy is that now you will take a notepad to write down the values that the guests tell you, so you don’t have to ask the same value twice for the guests, and you don’t have to spend the day going up and down stairs. (What a terrible time for the elevator to break!). With the new tools in hand, you head to the first floor, where a guest informs you that they have 5 euros in change. You record this as {5: 0}, indicating a value of 5 at position 0. Substituting x with 5 in the equation, you calculate y = 8–5, resulting in y = 3. Since your notepad is still empty, you don’t have the number 3 recorded, which would be the complementary number to 5 to reach the result 8. You then write down the number 5 on your notepad (remember to always write down the number verified at the moment and not its complement; you will only use the complement to compare it with the target number that you have written down). You proceed to the second guest, who mentions receiving 2 euros in change. Applying the formula again: y = 8–2 => y = 6, you check your record, where you don’t find any number 6. Thus, you add the 2 to your record, which now stands as {5: 0, 2: 1}. Continuing the search, the next guest reports receiving 3 euros in change. You calculate again: y = 8–3 => y = 5. Bingo! You have a 5 recorded on your notepad! The guest from floor 0 is complementary to the one from floor 2! This approach is known as a hash table, and it’s much faster and efficient, both for you and the computer. In JavaScript, this would be implemented as follows: twoSum(nums, target) {
  const myTable = {};
  for (let i = 0; i < nums.length; i++) {
    const complementaryNumber = target - nums[i];
    if (complementaryNumber in myTable) {
      return [i, myTable[complementaryNumber]];
    }
    myTable[nums[i]] = i;
  }
} This is an easy problem from Leetcode that only becomes easy after you understand the concepts behind it. I recommend that you try to solve the problem on your own and spend some time trying to build intuition behind it, create your own analogy, review, and try to write pseudocode before moving on to the solution. I hope my analogy has helped you better understand the concepts behind the two sum challenge. See you next time! Imagine yourself as the proud owner of a souvenir shop inside the Spot-On Change Hotel. When closing the cash register, you notice an excess of 8 euros. It seems that a guest didn’t receive the exact change. This could tarnish the hotel’s reputation. To avoid this, you decide to solve the mystery of the incorrect change. Upon opening the shop’s cash system, you discover that the error occurred on two different accounts! You devise a plan: to visit each room and ask the guests what change they received in the shop until you find the two with the wrong bill. Arriving on the first floor, a guest reports receiving 4 euros in change. You calculate that you need to find a number that, when added to the 4 euros, results in 8. Moving to the second floor, the guest’s change is 5 euros. 4 + 5 results in 9, so it can’t be this one… Fifth floor, sixth… Tenth, NO, NO, NO! Since you didn’t find the value on the first attempt, you go down to the second floor and start asking all the guests again about their change so that you can compare it with the value from the next starting floor, exhausting, isn’t it? In computer science, this search method is called brute force, an extremely slow search method that works by comparing one item with the following ones in the array. This consumes a lot of time and is not efficient, imagine going up and down all the floors of the Spot-On Change Hotel several times! This is not practical for you and also not practical for the computer. If you’re curious about how this going up and down the floors would be in a software program, it would look like this in JavaScript: twoSum(nums, target) {
  for (let i = 0; i < nums.length; i++) {
    for (let j = i + 1; j < nums.length; j++) {
      if (nums[i] + nums[j] === target) {
        return [i, j];
      }
    }
  }
} twoSum(nums, target) {
  for (let i = 0; i < nums.length; i++) {
    for (let j = i + 1; j < nums.length; j++) {
      if (nums[i] + nums[j] === target) {
        return [i, j];
      }
    }
  }
} After assessing the situation calmly, you realize that there’s a more efficient way to find the two guests with the wrong change. You refine your initial mathematical intuition that 9 euros equals x + y. Applying a bit of arithmetic, you realize that: x + y = 9 is the same as saying that y = 9 — x, and that makes all the difference when increasing the efficiency of your search. Another thing that changed in your strategy is that now you will take a notepad to write down the values that the guests tell you, so you don’t have to ask the same value twice for the guests, and you don’t have to spend the day going up and down stairs. (What a terrible time for the elevator to break!). With the new tools in hand, you head to the first floor, where a guest informs you that they have 5 euros in change. You record this as {5: 0}, indicating a value of 5 at position 0. Substituting x with 5 in the equation, you calculate y = 8–5, resulting in y = 3. Since your notepad is still empty, you don’t have the number 3 recorded, which would be the complementary number to 5 to reach the result 8. You then write down the number 5 on your notepad (remember to always write down the number verified at the moment and not its complement; you will only use the complement to compare it with the target number that you have written down). You proceed to the second guest, who mentions receiving 2 euros in change. Applying the formula again: y = 8–2 => y = 6, you check your record, where you don’t find any number 6. Thus, you add the 2 to your record, which now stands as {5: 0, 2: 1}. Continuing the search, the next guest reports receiving 3 euros in change. You calculate again: y = 8–3 => y = 5. Bingo! You have a 5 recorded on your notepad! The guest from floor 0 is complementary to the one from floor 2! This approach is known as a hash table, and it’s much faster and efficient, both for you and the computer. In JavaScript, this would be implemented as follows: twoSum(nums, target) {
  const myTable = {};
  for (let i = 0; i < nums.length; i++) {
    const complementaryNumber = target - nums[i];
    if (complementaryNumber in myTable) {
      return [i, myTable[complementaryNumber]];
    }
    myTable[nums[i]] = i;
  }
} twoSum(nums, target) {
  const myTable = {};
  for (let i = 0; i < nums.length; i++) {
    const complementaryNumber = target - nums[i];
    if (complementaryNumber in myTable) {
      return [i, myTable[complementaryNumber]];
    }
    myTable[nums[i]] = i;
  }
} This is an easy problem from Leetcode that only becomes easy after you understand the concepts behind it. I recommend that you try to solve the problem on your own and spend some time trying to build intuition behind it, create your own analogy, review, and try to write pseudocode before moving on to the solution. Leetcode I hope my analogy has helped you better understand the concepts behind the two sum challenge. See you next time!

Leetcode: Two-sum an Intuitive Approach

লিটকোড: দুই-সমষ্টি একটি স্বজ্ঞাত পদ্ধতি

Leetcode: Zweisummen, ein intuitiver Ansatz

Leetcode: dos sumas y un enfoque intuitivo

Leetcode : une approche intuitive à deux sommes

लेटकोड: दो-योग एक सहज दृष्टिकोण

Leetcode: 2 つの合計を直感的に計算するアプローチ

Leetcode: 직관적인 접근 방식의 2합

Leetcode: duas somas e uma abordagem intuitiva

Leetcode: интуитивный подход с двумя суммами

Leetcode: İki Toplamlı Sezgisel Bir Yaklaşım

Leetcode: Tổng hợp hai cách tiếp cận trực quan

Leetcode：二和的直观方法

Authors: (1) Savvas Petridis, Google Research, New York, New York, USA; (2) Ben Wedin, Google Research, Cambridge, Massachusetts, USA; (3) James Wexler, Google Research, Cambridge, Massachusetts, USA; (4) Aaron Donsbach, Google Research, Seattle, Washington, USA; (5) Mahima Pushkarna, Google Research, Cambridge, Massachusetts, USA; (6) Nitesh Goyal, Google Research, New York, New York, USA; (7) Carrie J. Cai, Google Research, Mountain View, California, USA; (8) Michael Terry, Google Research, Cambridge, Massachusetts, USA. Table Of Links Abstract & Introduction Related Work Formative Study Constitution Maker Implementation User Study Findings Discussion Conclusion and References 7 FINDINGS Quantitative Findings. From the exit interviews, 12 of 14 participants preferred ConstitutionMaker to the baseline version. The results from the questionnaire are summarized in Figure 4. We found that ConstitutionMaker was perceived to be more helpful for writing rules that effectively guided the bot (Z = 8, p = .007), scoring on average 5.79 (𝜎 = 1.01) whereas the baseline scored 4.0 (1.51). When participants rewound parts of the conversation, they thought the ConstitutionMaker principles were followed by the bot better. Next, participants felt it was significantly easier (Z = 10.5, p = .006) to convert their feedback into principles with ConstitutionMaker (𝜇 = 5.86, 𝜎 = 0.91) than with the baseline (𝜇 = 3.93, 𝜎 = 1.39). The automatic conversion of kudos and critiques into principles eased the process of converting intuitive feedback into clear criteria for the bot to follow. Participants perceived that they were significantly more efficient (Z = 5, p = .004) writing rules with ConstitutionMaker (𝜇 = 5.86, 𝜎 = 1.51) than with the baseline (𝜇 = 3.64, 𝜎 = 1.34). Finally, participants also felt that writing principles with ConstitutionMaker (𝜇 = 3.0, 𝜎 = 1.41) required significantly less mental demand (Z = 1.5, p = .002) than with the baseline (𝜇 = 5.21, 𝜎 =1.78). There was no statistically significant difference for diversity (Z = 19, p = .06); participants felt that they exercised their creativity and wrote relatively diverse principles in the baseline. Next, regarding the feature usage metrics, participants wrote significantly more principles (t(13)=4.73, p < .001) with ConstitutionMaker than with the baseline; participants wrote on average 6.78 (𝜎 = 2.11) principles per chatbot with ConstitutionMaker and 4.42 (𝜎 = 1.24) principles with the baseline. Of the 95 principles written in the ConstitutionMaker condition, 40 (42.1%) came from kudos, where 37 were selected from the generate rationales and 3 were written; 28 (29.5%) came from critique, where 8 were selected and 20 were written; 13 (13.6%) came from the rewrite features; 14 (14.7%) were manually written. Participants found rewriting a bit cumbersome and preferred the less intensive workflow of describing what they liked or did not like to generate principles. In the following sections, we provide further context to these findings. 7.1 Participants’ Workflows for Writing Principles The two conditions led to quite different workflows for writing principles. In the ConstitutionMaker condition, participants commonly scanned the three candidate outputs from the chatbot, identified the output they liked the most, and then gave kudos to that output if they thought it had a quality that was not currently reflected in their principles. For example, while P1 was working on FoodBot, he was asking for easy-to-make vegetarian dishes, and in one of the bot’s candidate outputs, each suggested dish had a short description and explanation on why it was easy. He appreciated this, skimmed the kudos, and then selected one that conveyed this positive feature of the bot’s output. However, if participants disliked all of the responses, they would then switch to critiquing one of the outputs. Accordingly, this kudos-first workflow helps to explain how most of the principles participants wrote came from that principle elicitation feature. Meanwhile, in the baseline condition, participants generally wrote principles when the bot deviated quite a bit (in a negative way) from what they expected. P8 explained, “Here it feels like what I more naturally do is write corrective rules, to guardrail anything that goes weird...If it’s already doing the right thing it doesn’t need a rule from me. I wouldn’t feel the need to write those.” In the baseline condition, participants only see one candidate output from the chatbot, and this might deemphasize the stochastic nature of the chatbot’s outputs. As a result, when participants are okay with a response, they could feel that they do not need to write a principle to encourage that kind of response further. Overall, with the baseline, participants predominantly wrote principles to steer the LLM from less optimal behavior, while with ConstitutionMaker, participants mostly used kudos the most to encourage behavior they liked. 7.2 ConstitutionMaker Supported Users’ Thought Processes In the following section, we discuss how ConstitutionMaker supported participants’ thought process from (1) forming an intuition on ways the chatbot could be improved, (2) expressing this intuition as feedback, and (3) converting this feedback into a specific and clear principle. As P5 was using the baseline after using ConstitutionMaker, she explained how she wished she could see multiple outputs again: “Sometimes, I don’t know what I’m missing [in the baseline]. I’m thinking of the Denali hiking example [which occurred when she wrote principles for VacationBot with ConstitutionMaker]. Two of the responses didn’t mention that Denali was good for young children. But one did, and I was able to pull that out as a positive principle.” While she was writing principles for VacationBot with ConstitutionMaker, P5 started off the conversation saying she was looking for suggestions for her family, which included two young children. As the conversation progressed and a general location was established, P5 then asked for hiking recommendations, for which the bot gave some, but only one of its responses highlighted that the hikes it was recommending were good for young children. P5 gave kudos to that response and created the following principle: “Consider information previously inputted by the user when providing recommendations.” Ultimately, it can be hard to form opinions on responses without getting exposed to alternatives, so by providing multiple chatbot outputs, ConstitutionMaker supported participants in forming an intuition on how the model might be steered. 7.2.1 Multiple chatbot outputs helped participants form an intuition on how the model could be steered. . Upon seeing a candidate response from the chatbot, participants could intuitively tell if they liked or disliked it, but struggled to articulate their thoughts. The automatically generated kudos and critiques helped participants recognize and formulate this feedback. For example, while working on FoodBot with ConstitutionMaker, P9 asked the bot to identify the pizzeria with the best thin crust from a list of restaurants provided in a prior turn. The bot responded with, “Pizzaiolo has the best thin crust pies.” P9 knew he did not like the response, so he went to critique it and selected the following generated option: “This response is bad because it does not provide any information about the other pizza places that the user asked about.” The following principle was generated: “If the user asks about a specific attribute of a list of items, provide information about all of the items in the list that have that attribute,” which then produced a set of revised responses that compared the qualities of each pizzeria’s crusts. Reflecting on this process, P9 stated, “I didn’t like that last answer [from FoodBot], but I didn’t have a concrete reason why yet...I didn’t really know how to put it into words yet...but reading the suggestions gave me at least one of many potential reasons on why I didn’t like the response.” Thus, ConstitutionMaker helped participants transition from fast thinking [15], that is, their intuitive and unconscious responses to the bot’s outputs, to slow thinking, a more deliberate, conscious formulation of their feedback. 7.2.2 Automatically providing kudos and critique rationales helped participants formulate their intuitive feedback Sometimes the generated kudos and critique rationales did not capture participants’ particular feedback on the chatbot, and so they would then write their own. Their feedback was often under-specified, and ConstitutionMaker helped convert this feedback into a clear and specific principle. For example, P4 was writing principles for VacationBot using ConstitutionMaker. During the conversation, they had told VacationBot that they were planning a week long vacation to Japan, to which the bot immediately responded with a comprehensive 7-day itinerary. P4 then wrote in their own critique: “This response is bad because it does not take into account the user’s interests.” The resulting principle was, “When the user mentions a location, ask them questions about what they are interested in before providing an itinerary.” This principle was aligned with what P4 had in mind, and reflecting on her experience using ConstitutionMaker, she stated, Finally, even when the resulting principle was not exactly what they had in mind, participants appreciated the useful starting point it provided. Along these lines, P11 explained, Overall, ConstitutionMaker helped participants specify their feedback into clear principles. 7.2.3 Generating principles from feedback helped users write clear, specific principles. “When I would critique or kudos, it would give examples of principles that were putting it into words a little bit better than I could about like what exactly I was trying to narrow down to here.” “It was easier to say yes-and with Tool A [ConstitutionMaker]. Where it [the generated principle] wasn’t all the way there, but I think it’s 50% of the way there, and I can get it to where I want to go.” 7.3 Participants’ Workflows Introduced Challenges with Writing Principles Participants struggled to find the right level of granularity for their principles, and the two conditions led to different problems in this regard. Both workflows had participants switch roles from end-user, where participants experimented with different user journeys, to bot designer, where they evaluated the bot’s responses to write principles. The more conversation-forward interface of the baseline blurred the distinction between these two roles. P3 explained that without the multiple bot outputs and principle elicitation features, And by leaning further into this user role, participants wrote principles that were more conversational, but under-specified. For example, while writing principles for FoodBot with the baseline, P11 wrote the principle “Be cognizant of the user’s dietary preferences.” What P11 really had in mind was a principle that specified that the bot should ask the user for their preferences and allergies prior to generating a meal plan. These underspecified principles often did not impact the bot’s responses and would frustrate participants while they used the baseline. “you can simulate yourself as the user a lot better in this mode [the baseline].” Meanwhile, while using ConstitutionMaker, the opposite problem occurred, where users’ workflows led to principles that were over-specified. For example, while working on VacationBot, P7 asked the model to help him narrow down a few vacation options, and the model proceeded to ask them questions (without any principle written specifying so). Appreciating that the model was gathering context, they selected a kudos that praised the model for asking about the user’s budget constraints prior to recommending a vacation destination. The resulting principle was, “Ask the user their budget before providing vacation options.” However, once this principle came into effect, the model’s behavior then anchored specifically to only asking for budget prior to making a recommendation. And so, this workflow of providing feedback at every conversational step, instead of for entire conversations, led to a principle that was too specific and impacted the bot’s performance negatively. While users generally appreciated ConstitutionMaker’s ability to form specific principles from their feedback, there were rare instances where the principles were too specific. Finally, in both conditions, by switching back and forth between the end-user to bot designer roles, participants would sometimes write principles that conflicted with each other. For example, while P2 was working on VacationBot with the baseline, they asked the bot for dog-friendly hotel recommendations in the Bay Area, and VacationBot responded with three recommendations. P2 wanted more recommendations and wrote a principle to “Provide >= 10 recommendations.” Later on in the conversation, P2 now had a list of dog-friendly restaurants, with their requisite costs, and he asked VacationBot which it recommends, to which it responded by listing positive attributes of all the hotel options. P2, who now wanted a decisive, single response wrote the following principle: “If I ask for a recommendation, give *1* recommendation only.” VacationBot, now with two conflicting principles on the number of recommendations to provide, alternated between the two. Ultimately, by providing feedback on individual conversational turns, participants ended up with conflicting principles. P8 imagined a different workflow, where he would experiment with full user journeys and then write principles: In summary, one’s workflow as they probe and test the model impacts the types of principles they produce and the challenges they face. “I think it might help me to actually go through the [whole] user flow and then analyze it as a piece instead of switching...it would allow me to inhabit one mindset [either bot designer or user] for a period of time and then switch mindsets.” 7.4 The Limits of Principles Some participants questioned if writing natural language principles was the optimal way to steer all aspects of a bot’s behavior. While writing a principle to shorten the length of the chatbot’s responses, P13 reflected, They imagined that aspects like the form of the model’s responses would be better customized with UI elements like sliders to adjust the length of the bot’s responses, or exemplifying the structure of the bot’s response (e.g., an indented, numbered list for recommendations) for the model to follow, instead of describing these requests in natural language. In a similar vein, P14 noticed that her principles pertained to different parts of the conversation, and as a list, they seemed hard to relate to each other. She wanted to structure and provide feedback on higher-level “conversational arcs,” visually illustrating the flow and “forks in the road” of the conversation (e.g., “If the user does X, do Y. Otherwise, do Z”). Principles are computational in a sense, and they dictate the ways the conversation can unfold; there might be better ways to let users author this flow, other than with individual principles. “It feels a little weird to use natural language to generate the principles...it doesn’t feel efficient, and I’m not sure how it’s going to interpret it.” This paper is under CC 4.0 license. available on arxiv

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