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If you just type “sales” or “teacher,” you’re going to get thousands of results that may not be what you’re looking for. On most job boards, you can enter “company:” followed by the name of the business you want to work at to eliminate any results that weren’t published by ...

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For job seekers without a college degree, Delta Air Lines, Hewlett Packard, Mastercard and Walmart, among others, led the way in helping workers make strides in their careers. · &quot;Companies play a big role both in who gets on the ladder, how people move up the ladder and whether they make ...

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So to get a piece of work done it is quite practical to put out a request on the internet and to offer it to an independent contractor or freelancer. By 2020, more than 40% of the US workforce will be so-called contingent workers, according to a study conducted by software company Intuit in ...

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is a productive tool for teams that puts all your actions, messages and files on one simple page. With Hive’s all-in-one dashboard, your team members have their actions prioritized automatically and everything they need to complete them. Hive interviewed , CEO at to know more. Kevin William David John Furneaux Hive Hi John, So tell us about Hive? Hive is a powerful project management platform for teams. It combines messaging, project management, file sharing onto one easy-to-use dashboard. Tell me more about why you are building this? Most tools only cover one area of collaboration — chat, planning, files — and force you to invest in a whole productivity stack. These leaves teams fractured and inefficient. I saw this over and over again as a consultant at and later as global head of customer success at . So I set out with my co-founder to create more integrated platform that is really easy to use. Capgemini Huddle Eric Typaldos That is what we have built in Hive. Manage your to-do list. Check on project progress. Chat with colleagues. Get updates from CRM. All. In. One. Place. It streamlines your workday. It makes it easier to drive projects forward. It’s also deadly easy to use, with lots of flexibility (kanban boards, calendar, lists) and available integrations. What’s unique about what you are building & why do you think companies should use Hive? Some of our primary competitors are , , but we also compete against more established tools like . Asana Basecamp Trello Microsoft Project Unlike these tools, Hive allows teams to plan and execute their projects in one place. So often, a project manager puts together the perfect project plan, but every time something changes they need to resend the file to everyone on the team. In Hive, a manager can make changes to the gantt chart and everyone on the team gets the updates in real-time on their “My Actions” list. Even better, we also have a chat accessible right next to your action tracking. So if someone asks you to do something in chat all you have to do is drag the chat onto your to-do list so you won’t forget. Can you tell us a bit about the different customer segments using Hive? Hive is a great place for any group of people looking for a better way to organize their work. So, we have a diverse set of customers ranging from small tech to large insurance companies to marketing agencies. startups However, Hive has resonated best with , operations, project management and design teams. These are teams with a lot to projects and people to manage at once, who aren’t being served well by any other tools out there. These are also teams that expect the same frictionless user experience they get in all their consumer facing apps. We provide everything they need in one place, and that is why they come to us from some of the other tools they are using. marketing How are your customers using Hive? Could you share a few different use cases? The Pin Factory group at is one great use case. The Pin Factory is responsible for creating pins for sales campaigns. Previously, sales team members would submit request via a which were then transferred to a google sheet and then assigned out by email. After assigned the requests, the team would collaborate and ask questions in slack. They were spread out between 4 different tools, which made it hard to keep track of it all. Pinterest Typeform Hive completely streamlined their workflow. Now, the sales team uses Hive Forms to request new pins. These requests drop straight into the Pin Factory’s Hive workspace and are assigned out with just a click of a button. Any discussions they need to have happen right in the chat on their Hive dashboard. Before they were using 4 different tools to get work done. Now they use one. That is the magic of Hive. Were there any early ‘growth hacks’ or tactics that have contributed to your current success? Integrations have been key for widening our reach. We particularly proud to be one of integrations partners and on the services store. Both organizations have complementary customers, and in these stores we catch them at the decision point. Zenefits WeWork Another thing that was important to us was identifying key verticals and regions we wanted to focus on. This has helped us build a name for ourselves and get more customer referrals. I also think one of the most important factors in our growth has been our focus on customers. We work hard to make sure our customers happy and almost all of our feature improvements have come directly from feedback from customers. Many of our assumptions about what would be helpful have been proven wrong from discussions with our customers. So many companies get caught up in the attitude of “I know better” and I think letting go of that has been key to our success. Our complete focus is on making it easier and more fun to do your work in Hive. What were some of the biggest challenges while building the product early on and how did you solve them? One of the biggest challenges was honing in on the experience that customers wanted. The key for us was setting up customer interviews with our early adopters and watching videos to see where people were struggling and constantly iterating to make it better. We are constantly adding new features or improving user experience. It is definitely a continuous process that will always be apart of the way our company works. FullStory What have been some of the most interesting integrations you’ve added? Are there any that have been particularly impactful for you? We have over 100 integrations available to accommodate all different needs. Some of our most popular , and for files, which allows users to have immediate access to their important documents in Hive. You can also connect your account and share Hive actions in your slack channels. Another integration we are excited about is Zenefits so that when an employee is hired they are automatically added into the company’s Hive workspace. Google Drive Dropbox Box Slack Before we end, what are the top products that you depend to run the company & how do you use them? is the central place where we handle all marketing and sales activities. From the beginning to the end of the customer lifecycle is handled in Hubspot. Hubspot We couldn’t live without . It’s live chat support is critical in helping us provide customers with the best possible experience, and it has really made it easy for a small team to provide best-in-class support. Intercom has been great for helping use understand user behavior and make it easy to identify what changes we need to make. Fullstory is where we handle all our subscription billing. It makes it easy to create invoices and adjust plan details. Chargebee is great for keeping a pulse on customer satisfaction. We can monitor the feedback and quickly identify any weak points so that they can be handled right away. Satismeter Originally published at siftery.com .

Everything your team needs to get work done faster on one page

Photo: www.unsplash.com Gritty Work + Dating = Slow Success Before everyone comes at my throat, let me clarify: The type of I’m talking about in this post is gritty work. The type of work no one wants to do, but I love. The work that calls for 12 hour days, and the type of work that has you jumping out of bed at 5:50 every morning while the rest of the world is still tucked in until 9:00. Now, let’s get started. work startup I’m on a startup journey right now. I’m young, and I’m learning how to manage time exceptionally while building this entity alongside being a full-time student. Now, with that being said, here’s a breakdown of my typical Monday: 5:50 AM — Wake up, shower, and get ready for the day. 6:20 AM — Start answering or sending out emails for the day. This includes networking, personal emails, etc. 7:00 AM — Start off coding on my latest project/improvements 8:00 AM — of the morning, good ol’ Visual Basic First class 9:00 AM — Quick, 20min breakfast 9:20 AM — Marketing, or coding 11:00 AM — , good ol’ Stats Second class 12:00 PM — , good ol’ Intro to Hardware Third class 1:00 PM — Jump on the bus to head downtown Grand Rapids for next class 1:30 PM — Coding or Marketing work in Grand Rapids 3:00 PM — , good ol’ business law Fourth Class 4:30 PM — Back to Allendale on the bus 5:00 PM — Dinner 5:30 PM — Relax for a little while, usually read 6:30 PM — Run/Workout 7:30 PM — HW, coding, emails, marketing etc. 10:00PM Bedtime So you can see what I’m talking about. I really only devote about an hour a day on my long days to take time for myself. I usually try and sneak in a workout at night, but you can only imagine what would happen if I had to factor in a date somewhere in there. Conclusion Dating is an extremely important thing. We all want to settle down and start a family, and I realize you have to typically date several people before you can find “the one.” In my case, my love and devotion to what I’m learning in class, and what I’m working on in my spare time just so happens to be much more important to me at this point than spending time dating around. I absolutely love meeting people and learning about how other people spend their time, but I figure there’ll be time for that late down the line. If you’re stressed on time with your latest project, consider giving up on dating for a little while. Perhaps consider to no go out partying next Saturday night, and get a large amount of work done instead. Everyone has time, we just have to be able to manage it properly. Your dreams will never become a reality if you don’t, at least, pursue them.

Trying to get work done? Stop Dating.

I have always been very conscious about how and where I spend my time. While I paid a lot of attention to the obvious ways to be more productive—create a distraction-free focused zone, limit time on social media, divide my work into small blocks of time, and take regular breaks to revive and rejuvenate—I missed a crucial element that often gets in the way of our productivity. Our brain. The human brain has this remarkable cognitive capacity to perform at levels far beyond what we consider our natural abilities, but it’s not without its limits. The that enable the brain to prioritize and process large amounts of information quickly also get in the way of our productivity. These mental shortcuts are the brain's way to conserve energy and work more efficiently. But they also lead to many thinking errors. cognitive biases Here are the 4 cognitive biases that have the biggest impact on our productivity—how we prioritize, make decisions, manage time, and get work done. Urgency effect Zeigarnik effect Complexity bias Planning fallacy Urgency effect When an urgent task comes knocking at the door, do you push important work aside because urgent tasks demand your immediate attention while important goals are far off into the future and can wait until later? Urgency effect makes us jump at every chance to solve time-sensitive urgent matters while putting off important work. Rationally our brain knows that important tasks have a larger payoff and bigger rewards in the long run, but under the effect of this bias, we fall victim to perceiving urgent as important. Urgent tasks keep us busy and make us feel important, but they also suck into our time. Prioritizing it at the expense of more impactful work keeps us trapped in an illusion of productivity. Why we fall for the urgency effect Important tasks typically have no specific deadline. They are time-consuming and complex as they often require looking into the future and proactively identifying its needs. Giving clarity to vague ideas, making crucial decisions, or laying out a future strategy is not only time-consuming, it’s also mentally taxing. Urgent tasks have easy-to-reach, visible goals. They bring instant gratification with a big hit of dopamine. Since dopamine serves as a reinforcement for remembering and repeating pleasurable experiences, you end up dedicating more time to urgent tasks at the expense of more impactful work. Continuously pushing important tasks to the back burner keeps us locked in a never-ending cycle of unproductive choices—dedicating less time to important work inevitably creates more urgency later. Important tasks become urgent in due course of time if delayed too much, not given proper attention, or carried out without real interest. Example of urgency effect Gina is the tech manager of the CRM team. The latest releases in ChatGPT and other AI innovations is becoming a threat to her business. But instead of spending time planning how to make them a part of their future strategy, Gina ends up spending most of her time on emails, meetings, and other urgent tasks. Her busyness keeps her locked in a cycle of unproductivity and inefficiency. Urgency effect makes her pay more attention to the work right in front of her—emails, chat notifications, customer escalations—while pushing important work aside. How to avoid urgency effect A great practice to avoid urgency bias involves using The Eisenhower Matrix for prioritization. To put the Eisenhower matrix to use, go through each task one by one and separate them into four possibilities: Important and Urgent (Quadrant 1): reduce time spent here Important and Not Urgent (Quadrant 2): consciously prioritize and schedule these tasks Not Important and Urgent (Quadrant 3): delegate these tasks Not Important and Not Urgent (Quadrant 4): declutter and eliminate. Consciously scheduling dedicated hours on the calendar to do important work makes it more likely that you attend to them without interruptions. A few other practices to adopt: Set aside specific blocks of time for responding to emails, chats, or other such tasks. Reduce time spent in meetings. Utilize your peak productivity period to do your most important work. Matching your energy with the physical and mental demands of work will enable you to do your best work making it more likely for you to continue instead of giving up. Set deadlines for important tasks and hold yourself accountable for meeting them. Zeigarnik effect Thoughts of unfinished tasks keep popping up in our head right when we get down to work or are trying hard to focus. *Emails we haven’t replied to.* Pending design to compete. Meetings to schedule. … so on and on. These intrusive thoughts that take away our attention even for a split second make it hard to concentrate and get any meaningful work done. Distractions from incomplete work prevent us from entering into a state of flow—which is when we are completely immersed in a task and the time seems to stand still. Flow minimizes distractions, prevents procrastination, and lead to high performance and productivity. Named after psychologist Zeigarnik who first discovered it, the effect refers to the tendency to remember unfinished or interrupted tasks better than completed ones. Letting our brain continually remind us that we haven’t done something is quite unpleasant and it can even lead to stress, anxiety, and burnout. Why we fall for the Zeigarnik effect Zeigarnik and her professor Kurt Lewin observed that their restaurant waiters remembered everyone’s orders despite never writing anything down. But as soon as the bill was paid, they had little or no memory of who their customers were or what they had ordered. This led to a series of experiments based on which Zeigarnik concluded that human minds treat tasks that have been completed differently from those that are still left to be completed. A task that has already been started establishes a task-specific tension, which keeps it at the forefront of our memory. The tension is relieved upon completion of the task but persists if it is interrupted or not yet completed. That’s why unfinished tasks keep coming back to haunt us. Look another way, these reminders can be useful to help us finish incomplete projects only if they do not spoil our attention right in the middle of another project. Attention is like energy in that without it no work can be done, and in doing work is dissipated. We create ourselves by how we use this energy. Memories, thoughts and feelings are all shaped by how we use it. And it is an energy under control, to do with as we please; hence attention is our most important tool in the task of improving the quality of experience. ― Mihaly Csikszentmihalyi Example of Zeigarnik effect Zeigarnik effect is used in gamification: Progress trackers informing users of how close they are to completing a task. For example, when users see a message like "Your profile is 34% complete", they are more likely to spend a few minutes providing all the missing details. This technique is used by to collect user information in a super smart way. LinkedIn Checklists that provide users with a clear step-by-step flow to onboard users faster and more effectively. Interrupted commercials are more likely to be remembered than those that are not due to the Zeigarnik effect. Advertisers use it to catch the attention and memory of viewers. How to avoid the Zeigarnik effect by Florida State University shows that planning work upfront and writing it down can free your mind from distracting thoughts about unfinished work. Have daily, weekly, and monthly rituals to review, prioritize, and plan what you intend to do. When you miss something and it pops up in your head, don’t leave it hanging there, immediately write it down. Research Moving tasks from your head onto paper relaxes your brain and helps you focus on the task at hand. A few other practices to adopt: Avoid procrastination by using the Zeigarnik effect to your advantage. Instead of putting things off because they are big or complex, simply take a very small step towards it. Once you get started, your brain will kick off the Zeigarnik effect enabling you to keep going till the end. Use the Pomodoro method to divide your work into small chunks of focused time. The tactical breaks in the Pomodoro method improve memory and keep productive momentum going. Complexity bias Given a choice between two competing solutions, we are likely to choose the more complex one. Jargon catches our attention over simple explanations. Difficult-to-execute strategies impress us over straightforward ones. Sophisticated products appear more authoritative while ordinary ones appear inferior. But complexity has many problems: Knowing upfront that something is difficult can prevent us from getting started. Obstacles and challenges along the way make it hard to persist and we may give up too soon. It can delay decision-making. It’s costly as it requires more time, effort and resources to get done. It can be potentially dangerous. Not understanding something fully can lead to wrong assumptions and conclusions. It can lead to hiding mistakes and fundamental flaws. Complexity bias is the tendency to prefer complicated explanations, solutions, and arguments over easy ones. Why we fall for the complexity bias Many people mistake simple for easy. Finding simple solutions to problems may sometimes require more effort—a conscious effort to dig deeper and give way to our creative mind, avoiding biases to cut through complexity and finding solutions that do not require too much scaffolding to support. Complexity in such cases could be an excuse to label the problem as too confusing and shove it aside. We choose complexity over simplicity for another reason: it’s falsely associated with expertise, innovation and authority. The more complex or advanced the approach is, the more superior it appears. Put another way, if a solution is too simple, we assume it won’t solve the problem. This makes us inject complexity and over complicate things instead of choosing a simpler approach. \As Edsger Wybe Dijkstra, a Dutch computer scientist once said “Simplicity is a great virtue but it requires hard work to achieve it and education to appreciate it. And to make matters worse: complexity sells better.” Example of complexity bias Jim got an opportunity to prepare and present the design of a new product to his entire team. He wanted the solution to stand out and establish credibility with others. But instead of asking the question “What problem is this product required to solve and how can I solve it in the simplest way possible?” he asked, “What problem is this product required to solve and how can I make it look good?” Trying to make the solution appealing led to poor choices: Instead of choosing a simple technology he understood well, he decided to use a new technology with no experience or expertise. He made complex architectural decisions to make the product look sophisticated. He introduced features that added little to no value to a customer but sounded interesting to implement. Complexity bias in his case led to poor decisions and terrible choices. How to avoid the complexity bias To counteract complexity bias, apply Occam’s razor. It is one of the most useful mental models to solve problems. Occam’s razor advocates simplicity by focusing on key elements of the problem, eliminating improbable options, and finding solutions with fewer assumptions. Another useful mental model to reduce complexity is first principles thinking. It requires breaking down a problem into its fundamental building blocks (its essential elements), asking powerful questions, getting down to the basic truth, separating facts from assumptions, and then constructing a view from the ground up. A few other practices to adopt: Since complexity bias shields you from seeking simple solutions, asking for others' opinions may be helpful. You may ask “Is my solution too complex or confusing?” Question your intent. Reframe the end goal to align it with the outcomes you wish to achieve. Show bias for action. Instead of being stuck in analysis paralysis, take a small step towards your goal, see how it works, and slowly improve it over time. Planning fallacy When it comes to setting deadlines, most of us are highly optimistic. Even if it’s something similar to what we have done in the past, we are still likely to underestimate how much time it will take to do it in the future. It took one week to finish a design proposal last time, but if you have to do it again, you’re positive it will get done in less than a week. It took more than a month for your new hires to get onboarded last time, but while planning for the new batch coming in next week, you allocated only 2 weeks. The planning fallacy is what makes us commit to overly optimistic timelines, miss those deadlines, and then drown in guilt, anxiety, and stress. Not factoring in realistic demands of the task leads to poor planning for the future. It harms your reputation and also breaks trust because when you miss those deadlines, others assume that you don’t take your commitments seriously. Why we fall for the planning fallacy When estimating the time it will take to complete a specific task, we ignore risks and other unlikely events that may prevent us from completing the task on time. Taking the best-case scenario into account and ignoring the obstacles we might encounter along the way leads to wishful thinking. We have the best intentions to get the work done quickly and efficiently, but good intentions aren’t always enough. Good planning needs good estimation skills. Another reason why we are highly optimistic about completing a specific job is our tendency to get stuck in the nitty gritty while ignoring the big picture. Not taking the big picture into account leads to poor estimation—we make wrong assumptions and ignore the time it will take to integrate our work into the bigger picture. We are also really bad at accurately judging our skills and abilities. Our enthusiasm to meet our goals adds to the planning fallacy. \Worst part? We don’t even learn from our past mistakes. Even when we can recognize past mistakes when we are overly optimistic, we keep on making the same mistakes in the future. We focus on our goal, anchor on our plan, and neglect relevant base rates, exposing ourselves to the planning fallacy. We focus on what we want to do and can do, neglecting the plans and skills of others. Both in explaining the past and in predicting the future, we focus on the causal role of skill and neglect the role of luck. We are therefore prone to an illusion of control. We focus on what we know and neglect what we do not know, which makes us overly confident in our beliefs. ― Daniel Kahneman Example of the planning fallacy Tina is working on the estimates of a new product. She has worked on a similar product in the past. The last time she built the product, it took her 3 months to complete. The project was initially estimated for 2 months but took an additional month due to requirements changes, a longer testing cycle, and other unforeseen issues. Tina has experience from the past that she should put to use to determine how long it will take to complete the current project. However, due to the planning fallacy, she commits to a 2-month deadline again. She justifies it by assuming that her experience from the past project will help her finish the tasks sooner while completely disregarding the additional time it will take to handle unexpected issues. How to avoid planning fallacy Break down the project into small parts and estimate how long each one will take. Doing this work upfront will make your effort estimates much closer to reality than being vaguely guided by hunch. Another great strategy is the one recommended by Daniel Kahneman - He suggests taking an outside view of your estimates by consulting others—asking questions and identifying problems and mistakes they made on similar projects in the past. You can’t do this for all your tasks but definitely do it for your most crucial ones. Irrespective of how good you’re at estimation, some unlikely event can crop up and make your project fall through the cracks. It isn’t possible to take every such scenario into account and plan for it. But what’s possible is to add a little buffer to your estimates—add 20% breathing room while considering the effort it takes to do something. Finally, and this is the most important one: implement a feedback loop in your process. Track your time. Make a note of how long it takes to do something. When you miss deadlines, identify what mistakes you made and what changes you need in your planning process to do better next time. When you’re conscious of how these biases—Urgency effect, Zeigarnik effect, Complexity bias and Planning fallacy—affect your time and apply the right strategies to overcome them, you can be your most productive self. Summary Most of us struggle with getting work done efficiently because we don’t pay attention to the cognitive biases that get in the way of using time productively. Urgency effect makes us waste time attending to urgent tasks at the cost of important tasks. Not paying attention to the future needs keeps us trapped in a cycle of unproductivity. The Zeigarnik effect prevents us from giving our best to the task at hand. When our mind keeps reminding us of incomplete or interrupted tasks, it’s hard to stay focused and pay attention. Complexity bias makes us add unnecessary complexity to solutions which increases the time, effort and cost to solve even simple problems. Planning fallacy tricks our mind to give highly optimistic estimates to achieve a certain goal despite our previous experience telling us that it will be impossible to achieve it. This story was previously published . here Follow me on or here for more stories. LinkedIn

Tackling the Saboteurs Within: 4 Cognitive Biases That Affect Your Productivity

এর মধ্যে নাশকতাকারীদের মোকাবেলা করা: 4টি জ্ঞানীয় পক্ষপাত যা আপনার উত্পাদনশীলতাকে প্রভাবিত করে

Die inneren Saboteure bekämpfen: 4 kognitive Vorurteile, die sich auf Ihre Produktivität auswirken

Enfrentando a los saboteadores internos: 4 sesgos cognitivos que afectan su productividad

S'attaquer aux saboteurs intérieurs : 4 biais cognitifs qui affectent votre productivité

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Борьба с внутренними саботажниками: 4 когнитивных искажения, которые влияют на вашу продуктивность

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解决内部破坏者：影响生产力的 4 种认知偏差

When you go about there are different approaches you can take to do so. building your own SaaS, If it’s your first time building a product, you start by picking one idea to develop. Take anything between 3-10 months to build a prototype or “ ” and then post about it everywhere on the internet. MVP But as you’ll eventually realize, the phrase “if you build it, they will come” is a total lie. It doesn’t have to be all doom and gloom though, in this article we’ll explore both approaches to building a SaaS, each with its pros and cons. You’ll find out when it’s better to use one method or the other. So, let’s dive in and take a look at the two ways you can build a SaaS. The Traditional “Private” Way of Building a SaaS If you have ever created something to promote online, whether that’s an e-book, a course, or an app, you are already acquainted with this method. However, for our purposes here, I’m talking specifically about solopreneurs and indie builders. This is the way that many people use when starting out. But it also applies to more experienced and more established builders. It also looks like the most reasonable way to build a SaaS. And for most people, this is the they know. only way It allows the creator to work and develop the idea without any intrusions and far from prying eyes. It provides the space to build an initial version, test it out, and iron out any bugs before the end users can find them. Many people build this way because they don’t want others to “steal their idea”. And so, they take however long to build something that’s good enough to put out and gather feedback from a small group of beta testers. However, the downside of this approach, regardless of whether it’s the first product or the 10th one, is the lack of feedback during the development phase. The initial idea in a lot of cases is not that similar to the end product. The first version of Twitter is not the same as it was 2 years after. Something similar happened to Instagram, it was created as an . However, the functionality of sharing photos was the most popular amongst the users. , that’s when it started getting thousands of users. app to share geolocated photos And when a small set of photo filters were added You see now that the initial idea can be one thing but it can change a lot after going through feedback from early users. A result of this lack of feedback is building a product that no one wants and no one pays for. A similar result is building something that does solve a specific need but doesn’t stand out in the market and can’t be discovered by its intended audience. The “Build in Public" Approach to SaaS Building This is the other side of the coin. With this approach, you don’t go into your cave for an extended period of time and then come out with creation and try to get it into the hands of as many people as possible. The name is a bit misleading and makes people think that they need to share everything that happens because it’s building “in public”. You don’t need to share or talk about that leads to the creation of the product. You can choose how public you want to get. every little detail every single event The idea is to find your ideal audience, get feedback from them early on, improve the initial idea with that feedback, and get people to care about what you’re building. This sounds like a better approach to building something in general, but with everything in life, there are also downsides. The most obvious one is that you’re putting yourself and your creation out in the open where everyone can see what you’re doing. This is uncomfortable for most people. You also need to be careful with what you’re sharing because if you overdo it, there are lurkers out there who won’t waste time copying what you’re building and will take away part of your userbase. For others, building in public makes you look like a novice that doesn’t know much and is just “throwing stuff at a wall to see what sticks”. This goes against what we have heard about being an “expert” in your field and having the credibility that you’ve “done the thing before” instead of it being your first time. Another downside for some people is that it will put them in a position of vulnerability, more so than they’re willing to be. And/or will expose them as “impostors”. That pressure can be too much for some to handle and they will either go back to doing things in private or try and share some things but won’t fully realize the advantages of the “build in public” approach. Where to Draw the Line Between the Two Methods of SaaS Building If you have heard about “build in public” before but haven’t really given it a try before, you should start with a project you are working on or plan to in the future. You don’t have to do it all by yourself though. If you are getting started and don’t know how to make the most out of it, there are communities out there (like HackerCabin or Build in Public Mastery) that are built around this concept. They are great places to start rather than DIY’ing it on social media. Going the “build in public” route can also be a good process of discovery. Both for knowing how to make a better product but also for more deeply and developing new skills (and also relationships!). knowing yourself Of course, if you’re working on something really important like helping people with a rare disease or creating water out of air particles… that’s something you can keep under wraps (at least until you get a patent for it). Building in public is not something that’s exclusive to SaaS or software products. It also applies for projects like books, courses, and even print-on demand. The important part here is not to share stuff for the sake of being “out there” or ticking off tasks from your marketing to-do list. People don’t really care about your product updates unless they’re close friends. When you build in public, of how you came up with ideas, how you implemented them in product, problems you came across and ; concepts others have a wrong view of and how your work can change them and provide a better view. share stories how you were able to solve them We are all naturally drawn to stories. And if the beginning is interesting and intriguing enough, we’ll want to see how they develop until the end. (That’s one of the reasons why new TV shows still come up.) Conclusion You now know that when it comes to building products to launch online, there’s no “one size fits all” way of doing so. You can build it on your own over a period of time and then, when you launch, it can have the results you want or it can flop. You can use the “build in public” approach and take a bit more time before the launch, but once you do, you know you’ll be launching something that helps people and have a waitlist of potential buyers instead of launching to crickets. And you can also play around with the amount of “public building” you want to do. Either be completely transparent on the process or dial it back and just share highlights and lessons learned. At the end of the day, the decision on which approach to choose is only yours. Take a look at your current situation, what your goals for the project are, what resources you have at your disposal (i.e. if you have the time, energy, and money for the project), and what a “successful” launch would look like. When considering these different factors, you can make a more informed decision on which approach to use when you set on the journey of building and eventually launching your next product. 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Choosing a SaaS Building Path: Build in Public or Private?

Why is Roblox Special? 

Debian GNU/Linux: Guide to Installation and Usage" by John Goerzen and Ossama Othman is part of the HackerNoon Books Series. You can jump to any chapter in this book . Introduction here 1. Introduction We’re glad to have this opportunity to introduce you to Debian! As we begin our journey down the road of GNU/Linux, we’d like to first talk a bit about what exactly Debian is—what it does, and how it fits in with the vast world of Free Software. Then, we talk a bit about the phenomenon that is Free Software and what it means for Debian and you. Finally, we close the chapter with a bit of information about this book itself. 1.1 What Is Debian? is a free operating system (OS) for your computer. An operating system is the set of basic programs and utilities that make your computer run. At the core of an operating system is the . The kernel is the most fundamental program on the computer: It does all the basic housekeeping and lets you start other programs. Debian uses the kernel, a completely free piece of software started by Linus Torvalds and supported by thousands of programmers worldwide. A large part of the basic tools that fill out the operating system come from the GNU Project , and these tools are also free. Debian kernel Linux [1] http://www.gnu.org/ [1] Another facet of an operating system is application software: programs that help get work done, from editing documents to running a business to playing games to writing more software. Debian comes with more than 1,500 (precompiled software bundled up in a nice format for easy installation on your machine)—all for free. packages The Debian system is a bit like a pyramid. At the base is Linux. On top of that are all the basic tools, mostly from GNU. Next is all the application software that you run on the computer; many of these are also from GNU. The Debian developers act as architects and coordinators—carefully organizing the system and fitting everything together into an integrated, stable operating system: Debian GNU/Linux. The design philosophy of GNU/Linux is to distribute its functionality into small, multipurpose parts. That way, you can easily achieve new functionality and new features by combining the small parts (programs) in new ways. Debian is like an erector set: You can build all sorts of things with it. When you’re using an operating system, you want to minimize the amount of work you put into getting your job done. Debian supplies many tools that can help, but only if you know what these tools do. Spending an hour trying to get something to work and then finally giving up isn’t very productive. This guide will teach you about the core tools that make up Debian: what tools to use in certain situations and how to tie these various tools together. 1.1.1 Who Creates Debian? Debian is an all-volunteer Internet-based development project. There are hundreds of volunteers working on it. Most are in charge of a small number of software packages and are very familiar with the software they package. These volunteers work together by following a strict set of guidelines governing how packages are assembled. These guidelines are developed cooperatively in discussions on Internet mailing lists. 1.2 A Multiuser, Multitasking Operating System As we mentioned earlier in section 1.1, the design of Debian GNU/Linux comes from the Unix operating system. Unlike common desktop operating systems such as DOS, Windows, and MacOS, GNU/Linux is usually found on large servers and systems. multiuser This means that Debian has features those other operating systems lack. It allows a large number of people to use the same computer at once, as long as each user has his or her own . To permit many users to work at once, Debian must allow many programs and applications to run simultaneously. This feature is called . terminal [2] multitasking A terminal is just a keyboard and a screen that are connected to the computer through the network, over a modem, or directly. You keyboard and monitor form a terminal that is directly attached to the computer: This special terminal is often called the . [2] console Much of the power (and complexity) of GNU/Linux systems stems from these two features. For example, the system must have a way to keep users from accidentally deleting each other’s files. The operating system also must coordinate the many programs running at once to ensure that they don’t all use the same resource, such as a hard drive, at the same time. If you keep in mind what Debian was originally designed to do, many aspects of it will make a lot more sense. You’ll learn to take advantage of the power of these features. 1.3 What Is Free Software? When Debian developers and users speak of “Free Software,” they refer to rather than price. Debian is free in this sense: You are free to modify and redistribute it and will always have access to the source code for this purpose. The Debian Free Software Guidelines describe in more detail exactly what is meant by “free.” The Free Software Foundation , originator of the GNU Project, is another excellent source of information. You can find a more detailed discussion of free software on the Debian web site . One of the most well-known works in this field is Richard M. Stallman’s essay, ; take a look at it for some insight into why we support Free Software as we do. Recently, some people have started calling Free Software “Open Source Software”; the two terms are interchangable. freedom [3] [4] [5] Why Software Should Be Free [6] http://www.debian.org/social_contract#guidelines [3] http://www.fsf.org/ [4] http://www.debian.org/ [5] http://www.fsf.org/philosophy/shouldbefree.html [6] You may wonder why would people spend hours of their own time writing software and carefully packaging it, only to give it all away. The answers are as varied as the people who contribute. Many believe in sharing information and having the freedom to cooperate with one another, and they feel that free software encourages this. A long tradition that upholds these values, sometimes called the Hacker Ethic, started in the 1950s. The Debian GNU/Linux Project was founded based on these Free Software ethics of freedom, sharing, and cooperation. [7] Note that the term “hacker” should not be confused with the term “cracker.” In short, a hacker is benevolent, whereas a cracker is generally considered malevolent. Movies and other forms of media many times incorrectly use the term “hacker” instead of “cracker.” [7] Others want to learn more about computers. More and more people are looking for ways to avoid the inflated price of proprietary software. A growing community contributes in appreciation for all the great free software they’ve received from others. Many in academia create free software to help get the results of their research into wider use. Businesses help maintain free software so they can have a say in how it develops—there’s no quicker way to get a new feature than to implement it yourself or hire a consultant to do so! Business is also interested in greater reliability and the ability to choose between support vendors. Still others see free software as a social good, democratizing access to information and preventing excessive centralization of the world’s information infrastructure. Of course, a lot of us just find it great fun. Debian is so committed to free software that we thought it would be useful if it was formalized in a document of some sort. Our Social Contract promises that Debian will always be 100% free software. When you install a package from the Debian main distribution, you can be sure it meets our Free Software Guidelines. [8] http://www.debian.org/social_contract [8] Although Debian believes in free software, there are cases where people want to put proprietary software on their machine. Whenever possible Debian will support this; though proprietary software is not included in the main distribution, it is sometimes available on the FTP site in the non-free directory, and there is a growing number of packages whose sole job is to install proprietary software we are not allowed to distribute ourselves. It is important to distinguish software from software. Proprietary software is non-free software; commercial software is software sold for money. Debian permits commercial software, but not proprietary software, to be a part of the main distribution. Remember that the phrase “free software” does not refer to price; it is quite possible to sell free software. For more clarification of the terminology, see http://www.opensource.org/or http://www.fsf.org/philosophy/categories.html. commercial proprietary 1.4 About This Book This book is aimed at readers who are new to Debian GNU/Linux. It assumes no prior knowledge of GNU/Linux or other Unix-like systems, but it does assume very basic general knowledge about computers and hardware; you should know what the basic parts of a computer are, and what one might use a computer to do. In general, this tutorial tries to help you understand what happens inside a Debian system. The idea is to empower you to solve new problems and get the most out of your computer. Thus there’s plenty of theory and fun facts thrown in with the “How To” aspects of the manual. We’d love to hear your comments about this book! You can reach the authors at debian-guide@complete.org. We’re especially interested in whether it was helpful to you and how we could make it better. Whether you have a comment or think this book is the greatest thing since sliced bread, please send us e-mail. Please do not send the authors technical questions about Debian, because there are other forums for that; see Appendix A on page [*] for more information on the documentation and getting help. Only send mail regarding the book itself to the above address. 1.4.1 How to Read This Book The best way to learn about almost any computer program is by using it. Most people find that reading a book without using the program isn’t beneficial. The best way to learn about Unix and GNU/Linux is by using them. Use GNU/Linux for everything you can. Feel free to experiment! Debian isn’t as intuitively obvious as some other operating systems. You will probably end up reading at least the first few chapters of this book. GNU/Linux’s power and complexity make it difficult to approach at first, but far more rewarding in the long run. The suggested way to learn is to read a little, and then play a little. Keep playing until you’re comfortable with the concepts, and then start skipping around in the book. You’ll find a variety of topics are covered, some of which you might find interesting. After a while, you should feel confident enough to start using commands without knowing exactly what they do. This is a good thing. Tip: If you ever mistakenly type a command or don’t know how to exit a program, press CTRL-c (the Ctrl key and the lowercase letter c pressed simultaneously). This will often stop the program. 1.4.2 Conventions Before going on, it’s important to be familiar with the typographical conventions used in this book. When you should simultaneously hold down multiple keys, a notation like CTRL-a will be used. This means “press the Ctrl key and press lowercase letter a.” Some keyboards have both Alt and Meta; most home computers have only Alt, but the Alt key behaves like a Meta key. So if you have no Meta key, try the Alt key instead. Keys like Alt and Meta are called keys because they change the meaning of standard keys like the letter A. Sometimes you need to hold down more than one modifier; for example, Meta-Ctrl-a means to simultaneously press Meta, Ctrl, and lowercase a. modifier Some keys have a special notation—for example, Ret (Return/Enter), Del (Delete or sometimes Backspace), Esc (Escape). These should be fairly self-explanatory. Spaces used instead of hyphens mean to press the keys in sequential order. For example, CTRL-a x RET means to simultaneously type Ctrl and lowercase a, followed by the letter x, followed by pressing Return. (On some keyboards, this key is labeled Enter. Same key, different name.) In sample sessions, bold face text denotes characters typed by the user, italicized text denotes comments about a given part of the sample session, and all other text is output from entering a command. For shorter commands, you’ll sometimes find that the command can be found within other text, highlighed with a monospace font. 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. John Goerzen and Ossama Othman (2004). Debian GNU/Linux : Guide to Installation and Usage. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/6527/pg6527-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

We’re glad to have this opportunity to introduce you to Debian!

Quite a few years ago, in a elsewhere, I had mentioned the following: previous article “The huge technological progress of the last decade addressed and greatly impacted the basic human need of communication. Websites, blogs, emails, text messages, Facebook, Snapchat, Slack and smartphones on the one hand and Google on the other as the dominant intermediary, all in essence addressing our need to communicate. I would refer to this as the ‘communication era’ that has “plateaued” in terms of potential truly disruptive innovation. The next era will be the ‘knowledge era’, where Artificial Intelligence (AI) will dominate.“ Now OpenAI has gulped the entire Web to usher in this “knowledge era” which could be seen as a new technology paradigm as it introduces Natural Language Processing and Inference ubiquitously. At my company Fortuit, we are now building Generative AI infused apps that solve real world problems. Inevitably, the questions that arise are: What is ChatGPT aka Generative AI What are the business benefits of integrating Generative AI? What are the Data Privacy implications? To what extent are businesses integrating Generative AI? Let’s go. WHAT IS GENERATIVE AI (like CHATGPT)? To put the discussion into context, it is important to describe what ChatGPT is in business and in more technical terms, as even within the software industry, AI and Machine Learning expertise is not ubiquitous. Business Perspective ChatGPT is a cutting-edge Generative AI tool designed to enhance customer interactions, automate repetitive tasks, and provide valuable insights. Example use cases include market research, customer support and sales / marketing efforts, allowing businesses to streamline communication processes, handle inquiries and even generate leads. Its ability to understand and generate human-like text makes it a powerful asset for businesses seeking to improve their market position and enhance their customer engagement strategies. Businesses can leverage ChatGPT to create interactive and dynamic customer experiences, ultimately leading to increased customer satisfaction and loyalty. Technical Perspective For developers, ChatGPT is a tool that provides natural language understanding and generation capabilities to create intelligent, conversational interfaces to their applications. ChatGPT is based on the Generative Pre-trained Transformer (GPT) architecture which is a type of deep learning (ML) model designed for natural language processing tasks. This Transformer architecture, referred to as a Large Language Model (LLM), was introduced in a paper titled “Attention Is All You Need” by Google engineers Vaswani et al. in 2017. In more detail, A GPT neural network architecture (LLM) is comprised of an “Encoder” and a “Decoder”. Encoder The encoder’s job is to read and understand user input, such as a sentence or a paragraph. It uses a mechanism called “self-attention” to capture relationships between words in the input, weighing the importance of each word as regards all other words, not concerning itself with the orders of the words as such. In this way contextual information and dependencies between the input words are captured. Decoder The decoder is used for generating text by predicting the next word given the input based and the previously generated sequence of words. Example To illustrate with a simple example: Input: “What is a Chabot” Encoder: · Input becomes: [0, 1 ,2, 3] · Accordingly, the calculated “attention” scores: [0.2, 0.3, 0.4, 0.7], indicating that the word “Chabot” commands the highest interest (attention) · The scores are multiplied by each word’s “vector”, where a vector is a numeric representation of a word in a vector “space” where similar words have similar vectors indicating contextual proximity (i.e., the words are usually seen together, like “hotel” and “travel”) · The Encoder’s outputs: [0.2 * vector (What), 0.3 * vector (is), 0.4 * vector (a), 0.7 * vector (Chabot)] Decoder · The Encoder’s output is the Decoder’s input · From the Encoders output, the decoder gets the probabilities of next potential words from the overall (English or other) vocabulary · From these words, the decoder’s mechanism selects the one with the highest probability to come next, in this case this word ‘System” · So, the generated response starts to become “What is a Chabot? … [system]” · This is repeated until the desired response length is reached. No more technical stuff from here on! THE BUSINESS BENEFITS OF INTEGRATING GENERATIVE AI The critical question for businesses is what this huge new technological opportunity means and what are the benefits for a company’s workings overall through the application of Generative AI. Furthermore, how can it seamlessly and safely be integrated into each business function with a view to improving performance and efficiency, connecting and centralizing these business processes? How to streamline Generative AI Integration into a coherent, simple long term AI Strategy? Business 101 To put the above in context, lets briefly take a step back to Business 101 and see what processes make up a business. Overall, business processes can be approximately divided into three categories: Core, Support and “Long Tail” Core Processes · Production · Sales and Marketing · Order Fulfillment · Customer Support · Product Development Support Processes · Human Resources (HR) & Recruiting · Finance · IT · Procurement Long Tail (everything else) A long-tail process is a custom / ad hoc workflow in response to evolving business needs, usually reflecting a gap between systems, apps, departments, or workflows, usually addressed through manual work or an informal workflow. Examples · Contract Management · Vendor approval · New hire request · Budget requests Application of Generative AI to Business Processes A huge opportunity exists for businesses to leapfrog competition by reimagining how humans get work done with generative AI applications at their side. Generative AI can and is being applied to business processes, unlocking novel use cases and also speeding up, scaling, and improving existing ones. Some potential business benefits Of Generative AI integration are: Automated Content Creation Personalized Customer Experiences Customer Service and Support Language Translation and Localization Cost Reduction Innovation and Idea Generation Overall, implementing generative AI enhances productivity, reduces costs, improves customer satisfaction, and unlocks innovation across various business function. But, to be more specific, below are some very beneficial use cases (among many more) in reference to the business processes described above. Core Business Process: Sales and Marketing A Sales AI Assistant to augment sales performance Imagine a customer sales call where the company’s “Sales AI Assistant” suggests upselling opportunities to the salesperson in real time based on the actual content of the conversation, drawing from CRM data, market trends, current news and social media influencer data. Before the call, the AI Assistant would provide a sales pitch draft. After the call, an assessment would be automatically generated that would allow the salesperson to provide feedback to the AI assistant with a view to helping it performance get better and better. The above does not mean replacing salespeople but teaming them up with generative AI. Core Business Process: Product Development Adding value to an existing product Imagine if for every specific product a company sells an employee could be assigned to guide the customer from initial use and un-boxing to trouble shooting and to best use guidelines. Customer satisfaction would sky rocket but of course the cost would be unsustainable. Imagine for example a specific Air Fryer product that has an accompanying specific AI Assistant implemented through a mobile app with speech to text and text to speech functionality that will guide product use from day one. Consider what this means for upselling, feedback, engagement, support and loyalty. This would be like hiring thousands of support employees, essentially for free. Support Business Process: Human Resources Company Culture and standards, training and on-boarding HR assistant A generative HR AI Assistant trained on proprietary knowledge such as company policies, customer interaction guidelines, and overall company culture and governance could provide continuous guidance and support to all company employees. The same assistant could act as a company Learning Management System (LMS), and a new employee on-boarding guidance counselor. Central AI Assistant — all processes, all assistants Importantly, in conjunction to applying generative AI to the various business processes described above, a core AI Assistant could be implemented as a “centralization” vehicle connecting, improving and monitoring all business processes and sub-assistants, so improving performance and efficiency and unlocking innovation across overall business functionality. Generative AI Implementation Modes All AI Assistants will have their own custom knowledge (LLM), and could potentially access data though API’s that connect to various company databases including ERP and CRM. All assistants would be implemented only as a Chat UX app accessible through mobile or the web with distinct authentication levels. All AI assistants would be minimal in terms of design and UX features, relying only on natural language chats sessions and a great amount of knowledge (unstructured) and data (structured). Cloud implementation · Custom LLM (hosted on the cloud on a service like Hugging Face Spaces which offers a simple way to host ML apps) · ChatGPT API leveraged to complement the Custom LLM as required. · AI Assistant app implemented on the cloud on a service like Azure or AWS. · AI Assistant implemented as an IOS or Android mobile app As regards Data Privacy, OpenAI recently launched ChatGPT Enterprise to address related concerns. ChatGPT Enterprise provides: · Data encryption “at rest” and “in transit” · Data privacy through AES 256 and TLS 1.2+ · SOC 2 compliance · Customer prompts and sensitive corporate data remain untapped for OpenAI model training In-house Implementation · LLM and Apps hosted within corporate IT infrastructure · No access to Chat GPT API or other GEN AI API’s. Hugging Face has over 300,000 models readily available, including exceptionally powerful large-language models, allowing businesses to deploy their own GPT privately and locally. Hybrid Implementation Internal use AI Assistants (like the HR example above), could be implemented and made accessible only within the corporate IT infrastructure. Non-public documents such as meeting minutes, legal documents, product specifications, technical documentation, R&D reports, business procedures, and so on could be made available only to internal AI Assistants. External use Assistants that rely on public company data clearly should use 3rd Party LLM services like ChatGPT, Google Bard and/or others. In theory, In-house implementations are safer but much more expensive. But, if in-house security is not at enterprise level (like the specifications mentioned above), is it really safer? DATA PRIVACY, COMPLIANCE AND SECURITY IMPLICATIONS OF GENERATIVE AI To be clear, Data Privacy and Compliance requirements have always been an important aspect of data processing and should be a priority for all business process and IT Systems. These issues and are not something that requires prioritization due to the recent advent of Generative AI technology. From a legal perspective, to date the United States lacks comprehensive, broadly applicable privacy protections like the European Union’s General Data Protection Regulation (“GDPR”) and its equivalent regulations in the United Kingdom and Switzerland, but does have a patchwork of federal and state laws addresses data privacy here at home. For example, The Virginia Consumer Data Protection Act (“VCDPA”) regulates only collection and use of personal information of consumers (employee data is exempt from regulatory requirements). The California Privacy Rights Act (“CPRA”) requires that notice of the business’s personal data handling practices be provided prior to or at the time of initial data collection. In terms of AI specific Regulation, there are various undergoing efforts (US, UK, EU), but it is a very difficult task. Innovation is stifled by over-regulation, and even if certain countries do over-regulate, others will clearly under-regulate. Let’s briefly look at the basic requirements for some of the regulatory directives mentioned above. European Union: GDPR (General Data Protection Act) Basic Principles o Lawful, fair and transparent processing o Limitation of purpose, data and storage o Data subject rights o Consent o Personal data breaches o Privacy by Design o Data Protection Impact Assessment o Data transfers o Data Protection Officer o Awareness and training United States: California Consumer Privacy Act (CCPA) (proxy for other potential regulation) Applies to businesses: o with an annual gross revenue of over $25 million o that gather, buy, sell, or receive personal information of over 50,000 California residents, households, or devices o derive more than 50% of annual revenue from selling the personal information of California residents Basic Principles o Right to Disclosure o Right to Access o Right to Contact Information. o Right to be Forgotten. o Opt-out of Data Sales and Marketing. o Right to Fair Treatment. o Periodic Privacy Policy Updates. United Kingdom: Data Protection Act Basic Principles o Used fairly, lawfully and transparently o Used for specified, explicit purposes o Used in a way that is adequate, relevant and limited to only what is necessary o Accurate and, where necessary, kept up to date o Kept for no longer than is necessary o Handled in a way that ensures appropriate security, including protection against unlawful or unauthorized processing, access, loss, destruction or damage Approaches to Generative AI Data Privacy, Compliance, Security Sandboxing Sandboxing is strategy to keep data safe when working with AI models. Sandboxing means creating a controlled environment within which a system or application operates. So a company can have internal apps working only with an internal (sandboxed) network (lan) environment. Data Obfuscation Obfuscation means replacing sensitive data with encrypted forms, sending this version to the LLM, and process the response by replacing the replaced data with the original version. For example, sending the following to ChatGPT: “Joe Smith lives at 4607 Rodeo LN Los Angeles CA 90016–5609 USA”. What is Joe’s current address?” would be translated to “<NAME-1>” lives at4607 Rodeo LN Los Angeles CA 90016–5609 USA. What is :<NAME-1>”’s current address?” The ChatGPT response “<NAME-1> lives at 4607 Rodeo LN Los Angeles CA 90016–5609 USA.” Would be converted to “Joe Smith lives at 4607 Rodeo LN Los Angeles CA 90016–5609 USA.” before being sent to the user. Moderation and Fact Checking API In all LLM use cases, a Moderation and Fact Checking API should be deployed. This would filter out a large range of inappropriate material in AI and/or user-generated content (UGC). At the same time, it would fact check both the input and output. LLMs do not recall facts (as databases do) but instead generate text that reads like human-written text that will always sound right but in some cases may be incorrect. This is known as hallucination. To mitigate this, in addition to the Moderation and Fact Checking API a containing certified company knowledge should be included and tapped into initially by the AI Assistant. custom LLM Use of Disclaimers As regards all AI applications, in addition to recorded user terms and conditions acceptance, disclaimers should clearly indicate that the content has been generated by AI and may not always be accurate and/or taken as medical, financial (or other) advice. Transparency and Data Best Practices Transparency about how Generative AI models have been trained is important. Users must always know what data might and might not be collected about them when using generative AI. There should always be an accessible mechanism for users to request data deletion or opt-out of certain data processing activities. Data de-identification and anonymization, identification of Personal Identifying Information (PII), data loss prevention and data minimization should always be considered when developing any *(Generative) AI application. TO WHAT EXTENT ARE BUSINESSES INTEGRATING GENERATIVE AI? OpenAI’s blog post reports ChatGPT’s impressive adoption. With over 80 percent uptake in Fortune 500 companies, industry leaders such as Block, Canva, and PwC are using ChatGPT Enterprise to expedite tasks ranging from coding to communications. Overall, AI integration is already underway in a significant number of businesses today with an ever-increasing trend as reflected in a recent Forbes Advisor Study shown below. According to this study, “a significant number of businesses (53%) apply AI to improve production processes, while 51% adopt AI for process automation and 52% utilize it for search engine optimization tasks such as keyword research. Companies are also leveraging AI for data aggregation (40%), idea generation (38%) and minimizing safety risks (38%). In addition, AI is being used to streamline internal communications, plans, presentations and reports (46%). Businesses employ AI for writing code (31%) and website copy (29%) as well.” Another study by revealed that 45 percent of top-level executives mentioned that exposure to ChatGPT had motivated them to boost their investments in AI. This trend is likely to continue with the introduction of ChatGPT Enterprise. Gartner Takeaway Generative AI is a major and rare opportunity for today’s businesses to transform themselves into less rigid and less bureaucratic entities, enabling a transition to a nimbler and more productive version of themselves, more akin to smaller niche companies. Current generative AI and other AI technologies have the potential to automate work activities that absorb a substantial percent of employees’ time today, allowing focus on more creative and productive activities. The potential benefits of Generative AI are significant. Risks and safeguards must be considered and implemented. In fact, integration is inevitable. P.S. Although I hold an MSc from QMW London in Artificial Intelligence — Advanced Methods in Computer Science and have technical expertise in ML Models, I am still continuously impressed by the workings of ChatGPT — GPT-4. I asked it to read this article, check grammar and spelling, tell me how much time would be required for someone to read it and to give me some NEW Gen AI insights. It answered saying that 12 minutes of reading would be required (stating the average read time per word), indicated grammar and spelling issues, and gave some great, deep insights referring to Reskilling, Impact on education, Cultural Implications, Accessibility/Inclusivity and Environmental Impact. I said “Thanks great answer” and it responded with “if there’s anything else I can help you with, feel free to ask, oh and happy reading”. From a technical perspective that “happy reading” part at the end is impressive, reflecting the extent of ChatGPT’s contextual understanding at more than one dimension, implying that AI systems are becoming increasingly sophisticated in their ability to comprehend and respond to human input, enhancing user experiences and interactions.

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