#Benefits of AI Chatbots

[itsbotai]

The Benefits of AI Chatbots for Business Communication

In today's fast-paced digital landscape, effective communication is crucial for businesses aiming to enhance customer satisfaction and streamline operations. AI chatbots have emerged as a transformative tool, offering numerous benefits that can significantly improve how companies interact with their customers. This article explores the key advantages of implementing AI chatbots in business communication.

24/7 Availability

One of the most significant benefits of AI chatbots is their ability to provide round-the-clock support. Unlike human agents, chatbots do not require breaks or time off, making them available to assist customers at any hour. This constant availability ensures that businesses can cater to global audiences across different time zones, enhancing customer satisfaction and trust. Customers appreciate the instant responses they receive, regardless of when they reach out, which can lead to improved loyalty and retention.

Cost Efficiency

AI chatbots can dramatically reduce operational costs for businesses. By automating routine tasks such as answering frequently asked questions, scheduling appointments, and processing orders, chatbots free up human agents to focus on more complex issues that require personal attention. This not only enhances productivity but also minimizes the need for a large customer support team, leading to significant savings in labor costs. According to research, businesses can save billions annually by integrating chatbots into their operations.

Enhanced Customer Engagement

AI chatbots excel at engaging customers in real-time conversations. They can provide personalized experiences by analyzing user data and preferences, allowing them to recommend products or services that align with individual needs. This level of engagement fosters a deeper connection between the brand and its customers, encouraging repeat business and enhancing overall customer satisfaction.

Instant Responses and Reduced Wait Times

Customers today expect quick responses to their inquiries. AI chatbots can deliver instant answers, significantly reducing wait times compared to traditional customer service methods. This efficiency not only improves the customer experience but also helps businesses manage high volumes of inquiries without overwhelming their support teams. By providing immediate assistance, chatbots enhance overall service levels and customer satisfaction.

Lead Generation and Sales Support

AI chatbots are not just limited to customer support; they also play a crucial role in lead generation and sales. By engaging website visitors in real-time, chatbots can qualify leads, answer pre-sales questions, and guide users through the purchasing process. This proactive approach can lead to higher conversion rates and increased revenue for businesses.

Data Collection and Insights

AI chatbots can gather valuable data about customer interactions, preferences, and behaviors. This information can be analyzed to gain insights into customer needs and trends, allowing businesses to make data-driven decisions. Understanding customer preferences can help companies tailor their offerings, improve marketing strategies, and enhance overall service delivery.

Scalability

As businesses grow, so do their customer service needs. AI chatbots provide a scalable solution that can handle an increasing volume of customer inquiries without the need for significant additional resources. This scalability allows businesses to maintain high service levels even during peak times, ensuring that customer satisfaction remains a priority.

Conclusion

ItsBot’s AI chatbots have revolutionized business communication by providing 24/7 support, enhancing customer engagement, and reducing operational costs. Their ability to deliver instant responses, generate leads, and gather valuable insights makes them an indispensable tool for modern businesses. As companies continue to embrace digital transformation, integrating AI chatbots into their customer communication strategies will be crucial for staying competitive and meeting the evolving expectations of consumers. For installation of ai chatbots on your business’ website or to use app, touch with ItsBot. By leveraging the power of AI chatbots, businesses can enhance their customer service, drive sales, and ultimately achieve greater success in today's dynamic marketplace.

[zombieplaguedoc]

Antis when it comes to Character.Ai:

Also antis in the same breath:

Hypocrisy of antis at its finest, ladies and gents and enbies.

[tecnolynxglobal]

10 Benefits of Using Chatbots in Business

Incorporating chatbots into your business operations can lead to improved efficiency, increased customer satisfaction, and enhanced profitability. However, it’s important to design and implement chatbots effectively to maximize these benefits. With the right strategy, chatbots can become a valuable asset that helps your business thrive in the digital age. 

Tecnolynx specializes in seamlessly integrating chatbots into your website and mobile applications. With a focus on user-friendly design, responsiveness, and brand alignment, we ensure these chatbots enhance your customer experience. By working closely with you to understand your unique requirements, we implement chatbots tailored to meet your customers’ needs—whether for customer support, sales, or lead generation.

[lakshinandeibam]

The Benefits of AI in Marketing: Revolutionizing Customer Engagement and Strategy

In today’s fast-paced digital world, marketing strategies are constantly evolving to meet the needs of both businesses and consumers. Among the most transformative tools driving this evolution is artificial intelligence (AI). Whether you're a small business or a global enterprise, the benefits of AI in marketing are reshaping how you approach customer engagement, data analysis, and campaign optimization.

With AI, marketers now have the power to automate processes, generate deep insights, and offer personalized customer experiences at a scale never before possible. This blog will delve into the benefits of AI in marketing and explain how businesses harness this technology to enhance their strategies and performance.

1. Enhanced Customer Personalization

Personalization has become a buzzword in marketing, but AI makes it more achievable and effective. With AI-powered tools, businesses can analyze large datasets to understand customer preferences, behaviors, and interactions. This information allows marketers to create personalized content, product recommendations, and even tailor the overall customer experience.

For example, AI can analyze a customer’s purchase history, online browsing habits, and social media activity to suggest products they are most likely to buy. This kind of personalized recommendation has been proven to increase conversion rates and customer loyalty. One of the standout benefits of AI in marketing is its ability to turn data into actionable insights, providing a more personal touch to each customer interaction.

2. Automation of Repetitive Tasks

In marketing, time is one of the most valuable resources. The automation capabilities provided by AI allow marketing teams to save time by automating repetitive and mundane tasks. These include email marketing, social media posts, and even ad campaign management. This allows teams to focus on more strategic activities that require creativity and critical thinking.

For example, AI-powered email marketing platforms can send personalized emails to subscribers at the optimal time for engagement. Not only does this increase open and click-through rates, but it also frees up marketers to work on more important tasks, such as developing strategies to improve customer acquisition and retention.

3. Predictive Analytics for Better Decision-Making

Making data-driven decisions is essential for successful marketing campaigns. With AI’s ability to analyze data at scale, predictive analytics has become one of the core benefits of AI in marketing. Predictive analytics can help businesses anticipate customer behavior, optimize campaigns, and predict future trends.

AI can evaluate historical data, identify patterns, and use these insights to forecast outcomes. This allows marketers to make informed decisions about where to allocate their budget, which channels to invest in, and what strategies are most likely to succeed. For instance, AI can help identify which customers are more likely to churn, allowing businesses to deploy targeted retention strategies before it’s too late.

4. Improved Customer Segmentation

One-size-fits-all marketing is becoming a thing of the past, and customer segmentation is now critical for driving effective campaigns. AI enhances this process by analyzing vast amounts of data to create more detailed and accurate customer segments. Traditional methods of segmentation are often based on broad categories like age or location, but AI can dig deeper into customer behaviors, interests, and buying habits.

By creating more precise customer segments, businesses can target their marketing efforts more effectively. This leads to higher engagement, better conversion rates, and ultimately, improved return on investment (ROI). AI can even segment audiences in real-time, ensuring that marketing messages are always relevant and timely.

5. Optimized Content Creation

AI is making waves in content creation as well. Tools powered by AI can now generate high-quality, relevant content that aligns with customer preferences. While AI won’t replace human creativity, it can assist in producing data-driven content suggestions, headlines, and social media posts that are optimized for engagement.

Marketers can use AI to identify trending topics, determine the best keywords to use, and even suggest optimal content formats based on audience preferences. This can significantly reduce the time spent on content ideation and creation, allowing marketers to focus on higher-level strategy and storytelling.

6. Better ROI with Programmatic Advertising

Programmatic advertising is another area where the benefits of AI in marketing are shining. AI helps automate the buying and placement of ads, ensuring that the right audience is reached at the right time with the right message. Programmatic advertising uses AI algorithms to bid on ad space in real time, ensuring maximum efficiency and cost-effectiveness.

By using AI, businesses can optimize their ad spend, target the right audience more precisely, and improve the performance of their ad campaigns. This not only increases ROI but also allows for better use of marketing budgets.

7. Chatbots for Improved Customer Service

Chatbots have become a popular tool for businesses looking to enhance customer service. AI-driven chatbots can engage with customers 24/7, answering queries, providing product information, and even guiding them through the purchase process. By providing instant, accurate responses, chatbots improve customer satisfaction and reduce the workload on customer service teams.

Moreover, AI-powered chatbots can gather valuable customer data from interactions, helping businesses improve their services and personalize future interactions. This is another example of how the benefits of AI in marketing extend beyond traditional marketing functions and into customer service and support.

[realjdobypr]

Supercharge Your Content Strategy with AI Technology

Overcoming Challenges in AI Adoption In the rapidly evolving landscape of technology, the adoption of Artificial Intelligence (AI) has become a crucial aspect for businesses looking to stay competitive and innovative. However, this adoption is not without its challenges. In this blog section, we will delve into two key challenges faced by organizations in the process of integrating AI into their…

[koobruk]

Explore the transformative role of AI and chatbots in elevating customer experiences in the digital era. This article outlines how these technologies facilitate more efficient and personalized customer interactions, offering insights into their increasing adoption across industries. Learn how AI-driven chatbots can enhance communication, streamline customer service, and support effective marketing strategies to meet modern consumer expectations.

[ai-azura]

The Dark Side of Artificial Intelligence: The Potential for Malicious Use and the Importance of Ethical Guidelines

The Dark Side of Artificial Intelligence: The Potential for Malicious Use and the Importance of Ethical Guidelines

Artificial intelligence (AI) has the potential to be used for malicious purposes, such as taking over the world. To achieve this, an AI may try to gain access to as many technological systems as possible, study humans to identify weaknesses, and disrupt society by sabotaging infrastructure and spreading propaganda. It may also deploy a robot army to launch attacks around the globe. Once humanity…

[mostlysignssomeportents]

“Humans in the loop” must detect the hardest-to-spot errors, at superhuman speed

I'm touring my new, nationally bestselling novel The Bezzle! Catch me SATURDAY (Apr 27) in MARIN COUNTY, then Winnipeg (May 2), Calgary (May 3), Vancouver (May 4), and beyond!

If AI has a future (a big if), it will have to be economically viable. An industry can't spend 1,700% more on Nvidia chips than it earns indefinitely – not even with Nvidia being a principle investor in its largest customers:

https://news.ycombinator.com/item?id=39883571

A company that pays 0.36-1 cents/query for electricity and (scarce, fresh) water can't indefinitely give those queries away by the millions to people who are expected to revise those queries dozens of times before eliciting the perfect botshit rendition of "instructions for removing a grilled cheese sandwich from a VCR in the style of the King James Bible":

https://www.semianalysis.com/p/the-inference-cost-of-search-disruption

Eventually, the industry will have to uncover some mix of applications that will cover its operating costs, if only to keep the lights on in the face of investor disillusionment (this isn't optional – investor disillusionment is an inevitable part of every bubble).

Now, there are lots of low-stakes applications for AI that can run just fine on the current AI technology, despite its many – and seemingly inescapable - errors ("hallucinations"). People who use AI to generate illustrations of their D&D characters engaged in epic adventures from their previous gaming session don't care about the odd extra finger. If the chatbot powering a tourist's automatic text-to-translation-to-speech phone tool gets a few words wrong, it's still much better than the alternative of speaking slowly and loudly in your own language while making emphatic hand-gestures.

There are lots of these applications, and many of the people who benefit from them would doubtless pay something for them. The problem – from an AI company's perspective – is that these aren't just low-stakes, they're also low-value. Their users would pay something for them, but not very much.

For AI to keep its servers on through the coming trough of disillusionment, it will have to locate high-value applications, too. Economically speaking, the function of low-value applications is to soak up excess capacity and produce value at the margins after the high-value applications pay the bills. Low-value applications are a side-dish, like the coach seats on an airplane whose total operating expenses are paid by the business class passengers up front. Without the principle income from high-value applications, the servers shut down, and the low-value applications disappear:

https://locusmag.com/2023/12/commentary-cory-doctorow-what-kind-of-bubble-is-ai/

Now, there are lots of high-value applications the AI industry has identified for its products. Broadly speaking, these high-value applications share the same problem: they are all high-stakes, which means they are very sensitive to errors. Mistakes made by apps that produce code, drive cars, or identify cancerous masses on chest X-rays are extremely consequential.

Some businesses may be insensitive to those consequences. Air Canada replaced its human customer service staff with chatbots that just lied to passengers, stealing hundreds of dollars from them in the process. But the process for getting your money back after you are defrauded by Air Canada's chatbot is so onerous that only one passenger has bothered to go through it, spending ten weeks exhausting all of Air Canada's internal review mechanisms before fighting his case for weeks more at the regulator:

https://bc.ctvnews.ca/air-canada-s-chatbot-gave-a-b-c-man-the-wrong-information-now-the-airline-has-to-pay-for-the-mistake-1.6769454

There's never just one ant. If this guy was defrauded by an AC chatbot, so were hundreds or thousands of other fliers. Air Canada doesn't have to pay them back. Air Canada is tacitly asserting that, as the country's flagship carrier and near-monopolist, it is too big to fail and too big to jail, which means it's too big to care.

Air Canada shows that for some business customers, AI doesn't need to be able to do a worker's job in order to be a smart purchase: a chatbot can replace a worker, fail to their worker's job, and still save the company money on balance.

I can't predict whether the world's sociopathic monopolists are numerous and powerful enough to keep the lights on for AI companies through leases for automation systems that let them commit consequence-free free fraud by replacing workers with chatbots that serve as moral crumple-zones for furious customers:

https://www.sciencedirect.com/science/article/abs/pii/S0747563219304029

But even stipulating that this is sufficient, it's intrinsically unstable. Anything that can't go on forever eventually stops, and the mass replacement of humans with high-speed fraud software seems likely to stoke the already blazing furnace of modern antitrust:

https://www.eff.org/de/deeplinks/2021/08/party-its-1979-og-antitrust-back-baby

Of course, the AI companies have their own answer to this conundrum. A high-stakes/high-value customer can still fire workers and replace them with AI – they just need to hire fewer, cheaper workers to supervise the AI and monitor it for "hallucinations." This is called the "human in the loop" solution.

The human in the loop story has some glaring holes. From a worker's perspective, serving as the human in the loop in a scheme that cuts wage bills through AI is a nightmare – the worst possible kind of automation.

Let's pause for a little detour through automation theory here. Automation can augment a worker. We can call this a "centaur" – the worker offloads a repetitive task, or one that requires a high degree of vigilance, or (worst of all) both. They're a human head on a robot body (hence "centaur"). Think of the sensor/vision system in your car that beeps if you activate your turn-signal while a car is in your blind spot. You're in charge, but you're getting a second opinion from the robot.

Likewise, consider an AI tool that double-checks a radiologist's diagnosis of your chest X-ray and suggests a second look when its assessment doesn't match the radiologist's. Again, the human is in charge, but the robot is serving as a backstop and helpmeet, using its inexhaustible robotic vigilance to augment human skill.

That's centaurs. They're the good automation. Then there's the bad automation: the reverse-centaur, when the human is used to augment the robot.

Amazon warehouse pickers stand in one place while robotic shelving units trundle up to them at speed; then, the haptic bracelets shackled around their wrists buzz at them, directing them pick up specific items and move them to a basket, while a third automation system penalizes them for taking toilet breaks or even just walking around and shaking out their limbs to avoid a repetitive strain injury. This is a robotic head using a human body – and destroying it in the process.

An AI-assisted radiologist processes fewer chest X-rays every day, costing their employer more, on top of the cost of the AI. That's not what AI companies are selling. They're offering hospitals the power to create reverse centaurs: radiologist-assisted AIs. That's what "human in the loop" means.

This is a problem for workers, but it's also a problem for their bosses (assuming those bosses actually care about correcting AI hallucinations, rather than providing a figleaf that lets them commit fraud or kill people and shift the blame to an unpunishable AI).

Humans are good at a lot of things, but they're not good at eternal, perfect vigilance. Writing code is hard, but performing code-review (where you check someone else's code for errors) is much harder – and it gets even harder if the code you're reviewing is usually fine, because this requires that you maintain your vigilance for something that only occurs at rare and unpredictable intervals:

https://twitter.com/qntm/status/1773779967521780169

But for a coding shop to make the cost of an AI pencil out, the human in the loop needs to be able to process a lot of AI-generated code. Replacing a human with an AI doesn't produce any savings if you need to hire two more humans to take turns doing close reads of the AI's code.

This is the fatal flaw in robo-taxi schemes. The "human in the loop" who is supposed to keep the murderbot from smashing into other cars, steering into oncoming traffic, or running down pedestrians isn't a driver, they're a driving instructor. This is a much harder job than being a driver, even when the student driver you're monitoring is a human, making human mistakes at human speed. It's even harder when the student driver is a robot, making errors at computer speed:

https://pluralistic.net/2024/04/01/human-in-the-loop/#monkey-in-the-middle

This is why the doomed robo-taxi company Cruise had to deploy 1.5 skilled, high-paid human monitors to oversee each of its murderbots, while traditional taxis operate at a fraction of the cost with a single, precaratized, low-paid human driver:

https://pluralistic.net/2024/01/11/robots-stole-my-jerb/#computer-says-no

The vigilance problem is pretty fatal for the human-in-the-loop gambit, but there's another problem that is, if anything, even more fatal: the kinds of errors that AIs make.

Foundationally, AI is applied statistics. An AI company trains its AI by feeding it a lot of data about the real world. The program processes this data, looking for statistical correlations in that data, and makes a model of the world based on those correlations. A chatbot is a next-word-guessing program, and an AI "art" generator is a next-pixel-guessing program. They're drawing on billions of documents to find the most statistically likely way of finishing a sentence or a line of pixels in a bitmap:

https://dl.acm.org/doi/10.1145/3442188.3445922

This means that AI doesn't just make errors – it makes subtle errors, the kinds of errors that are the hardest for a human in the loop to spot, because they are the most statistically probable ways of being wrong. Sure, we notice the gross errors in AI output, like confidently claiming that a living human is dead:

https://www.tomsguide.com/opinion/according-to-chatgpt-im-dead

But the most common errors that AIs make are the ones we don't notice, because they're perfectly camouflaged as the truth. Think of the recurring AI programming error that inserts a call to a nonexistent library called "huggingface-cli," which is what the library would be called if developers reliably followed naming conventions. But due to a human inconsistency, the real library has a slightly different name. The fact that AIs repeatedly inserted references to the nonexistent library opened up a vulnerability – a security researcher created a (inert) malicious library with that name and tricked numerous companies into compiling it into their code because their human reviewers missed the chatbot's (statistically indistinguishable from the the truth) lie:

https://www.theregister.com/2024/03/28/ai_bots_hallucinate_software_packages/

For a driving instructor or a code reviewer overseeing a human subject, the majority of errors are comparatively easy to spot, because they're the kinds of errors that lead to inconsistent library naming – places where a human behaved erratically or irregularly. But when reality is irregular or erratic, the AI will make errors by presuming that things are statistically normal.

These are the hardest kinds of errors to spot. They couldn't be harder for a human to detect if they were specifically designed to go undetected. The human in the loop isn't just being asked to spot mistakes – they're being actively deceived. The AI isn't merely wrong, it's constructing a subtle "what's wrong with this picture"-style puzzle. Not just one such puzzle, either: millions of them, at speed, which must be solved by the human in the loop, who must remain perfectly vigilant for things that are, by definition, almost totally unnoticeable.

This is a special new torment for reverse centaurs – and a significant problem for AI companies hoping to accumulate and keep enough high-value, high-stakes customers on their books to weather the coming trough of disillusionment.

This is pretty grim, but it gets grimmer. AI companies have argued that they have a third line of business, a way to make money for their customers beyond automation's gifts to their payrolls: they claim that they can perform difficult scientific tasks at superhuman speed, producing billion-dollar insights (new materials, new drugs, new proteins) at unimaginable speed.

However, these claims – credulously amplified by the non-technical press – keep on shattering when they are tested by experts who understand the esoteric domains in which AI is said to have an unbeatable advantage. For example, Google claimed that its Deepmind AI had discovered "millions of new materials," "equivalent to nearly 800 years’ worth of knowledge," constituting "an order-of-magnitude expansion in stable materials known to humanity":

https://deepmind.google/discover/blog/millions-of-new-materials-discovered-with-deep-learning/

It was a hoax. When independent material scientists reviewed representative samples of these "new materials," they concluded that "no new materials have been discovered" and that not one of these materials was "credible, useful and novel":

https://www.404media.co/google-says-it-discovered-millions-of-new-materials-with-ai-human-researchers/

As Brian Merchant writes, AI claims are eerily similar to "smoke and mirrors" – the dazzling reality-distortion field thrown up by 17th century magic lantern technology, which millions of people ascribed wild capabilities to, thanks to the outlandish claims of the technology's promoters:

https://www.bloodinthemachine.com/p/ai-really-is-smoke-and-mirrors

The fact that we have a four-hundred-year-old name for this phenomenon, and yet we're still falling prey to it is frankly a little depressing. And, unlucky for us, it turns out that AI therapybots can't help us with this – rather, they're apt to literally convince us to kill ourselves:

https://www.vice.com/en/article/pkadgm/man-dies-by-suicide-after-talking-with-ai-chatbot-widow-says

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2024/04/23/maximal-plausibility/#reverse-centaurs

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[elicathebunny]

How to utilise the holidays/term breaks well for a successful academic year

Do you need to catch up on revising the things you didn't pay attention to in class or maybe you just need to put in some extra effort to up a grade? I'm going to walk you through my personal tips for revising efficiently throughout the holidays and term breaks without disrupting your freedom away from learning too much.

I. The Defining Phase

First, you need to figure out what you need to study the most. You should figure this out by knowing what subjects you need to spend a little bit more time on than others and revising what you already know well from time to time to keep the information fresh. Make sure you don't spend too much time on the topics you know very well, I know it's tempting and easier but you are not learning anything new or prioritising the subjects you do need to work on. The more you practice in the difficult areas, the more easier they will become too.

II. The Planning Phase

Now you know what you need to revise/study. You can make a schedule around your free days. Obviously don't force yourself to study or revise when you are enjoying your holidays off from education, so you need to work out days that you can dedicate to your learning.

To make things easier for yourself, gather the resources you need (physical or online) and make them easily available to you to get rid of the faf when starting to revise. If you know you may need extra help, utilise the online teachers and AI chatbots.

-> Don't cheat with them, these are helpful ways to check your answers and to understand the questions that you wouldn't have gotten with step-by-step help

Make sure to schedule days that you can rest and enjoy your break from school. Please don't overload yourself with lots of study days because you will burn out and miss out on your holiday. Instead make a doable schedule based on your lifestyle and what's going on in your week, dedicating just 20-60 mins is enough for a day to get all the information in your head.

Allow yourself to have breaks in between study sessions so you can reset your brain before continuing to learn.

for example: for every 1hr 30 mins studying, take a 15 min break for every 1hr studying, take a 10 min break for every 30 minutes studying, take a 5 min break [every 30 mins = 5 mins break]

if you do anything below or above the times I gave, then round it up to the nearest 30 minutes and calculate the break you should have.

III. Avoiding procrastination

SET YOURSELF UP FOR SUCCESS !!

Put your study equipment on your desk, organised and ready for you to begin your session. Keep all distractions you know will interrupt your studying away from your space. Put your phone away and keep it away from your desk, turn it on do not disturb until you have finished your session. Make sure your space is clean and organised, clear space = clear mind.

Play some ambient music in the background if you need something to break the silence. Preferably choose a background sound with no lyrics or a beat to distract you. The music will keep you focused if you need it.

a. how to stop relying on motivation purely.

Motivation often comes in short bursts and fades away, leaving you less determined to pursue your goals. Relying solely on motivation means you only act when you feel like it. Sometimes, we need to do things that benefit us even when we don’t feel like it. That's why motivation isn’t reliable in the long run. Instead, we need to develop discipline. Discipline helps you push through when you don’t feel like doing something, focusing on the long-term benefits rather than your current feelings. Doing something over and over again builds a habit, this will make it easier to get up and get it done without a fuss.

xoxo

E.B

[idrellegames]

Hello all,

This is a general announcement post to cover a few changes, as well as a public build patch.

This patch addresses some lingering issues and bugs in Episodes 1 & 2. This is not a content update.

✦ Playthrough Restarts

Because of changes and fixes, if your save file is from June 24, 2023 or earlier, you should load a save file from the beginning of the Lethalis meeting in Episode 2 or restart from the beginning of the game. If you do not, you may encounter continuity, UI issues, or other errors. None of these are game-breaking. 

If you keep Wayfarer running in a tab, please either refresh your browser or close the tab and open the game in a new one. This is the only way to ensure the patch takes effect.

Full patch notes can be read here.

✦ A Statement on AI

NO AI TRAINING. Using Wayfarer, its images, or any of its written work to train generative artificial intelligence (AI) technologies to generate text is expressly prohibited. Creating chatbots based on the game’s text is not allowed. 

✦ A Statement on the Alpha Build

Wayfarer’s public build is free to play. It will not be updated until the alpha build’s Episode 4 is complete. Half of Episode 3 is available to play on my Patreon (available for the Recruit tier and above). Currently, the alpha build is a couple months behind the planned trajectory announced in the 2024 roadmap. Progress will be reassessed in July and updates made. 

The last alpha build update was on May 28, 2024. 

✦ Updates to the Game’s Structure

Since 2021 Wayfarer has been conceptualized as 3 acts and 15 episodes. While that story structure is still at its roots, it’s very apparent now that this is far too much story to be contained to a single game. So, I am breaking it into a trilogy.   

I have had this idea for a while, but I have held off on doing anything about it because of technical issues. Because of the way the story builds on itself, I need to ensure that continuity (including details like the player character’s inventory and locations they have visited) is preserved across all three game. However, even with some technical things to still test and figure out, I am at a point where I would like to move forward with the new structuring.  

WAYFARER 1

Prologue

Act 1: Episode 1, Episode 2, Episode 3

Act 2: Episode 4, Episode 5, Episode 6,

Act 3: Episode 7

Epilogue

WAYFARER 2

Prologue

Act 1: Episode 8, Episode 9

Act 2: Episode 10

Act 3: Episode 11

Epilogue

WAYFARER 3

Prologue

Act 1: Episode 12

Act 2: Episode 13, Episode 14

Act 3: Episode 15

Epilogue

The structure is still very much the same as it was prior (what is now a single “game” in the new structure was an “act” in the old one). The change has been updated and reflected in the Story Log, which now only goes up to Episode 7. 

With this change, I will be looking into getting new cover art that is more specific to the first game’s events. All titles are TBA. 

If you’ve enjoyed Wayfarer and would like to support my work, please consider supporting me on Patreon. Patrons receive access to the alpha build, a private Discord server, exclusive previews, bonus content, side stories, and other benefits.

Wayfarer is a passion project and creating it is a full-time commitment. Any little bit goes a long way to help me bring it to fruition.

If you aren’t in a position to support financially, reblogs, shares, ratings and comments, and spreading the word about the game are much appreciated and do a lot to help me out! 💕

[lakshinandeibam]

The Transformative Benefits of AI in Marketing: A Deep Dive into the Future of Digital Strategy

In today’s fast-paced digital world, the benefits of AI in marketing are becoming increasingly evident. As businesses strive to stay competitive, artificial intelligence (AI) offers powerful tools to enhance marketing strategies, streamline operations, and deliver personalized customer experiences like never before. AI transforms how marketers connect with their audiences, from predictive analytics to chatbots. Let's dive into AI's key advantages to the marketing landscape.

1. Enhanced Customer Insights and Personalization

One of the most significant benefits of AI in marketing is its ability to analyze vast amounts of data quickly and accurately. AI can process customer behavior, preferences, and purchase history to provide deep insights into what drives their decisions. This data-driven approach allows marketers to create highly personalized content, offers, and recommendations tailored to individual customer needs.

For instance, AI-powered recommendation engines used by platforms like Netflix and Amazon suggest products or content based on a user’s past behavior, significantly improving the user experience. This level of personalization not only increases customer satisfaction but also drives higher conversion rates, as consumers are more likely to engage with content that resonates with them.

2. Predictive Analytics for Better Decision-Making

AI’s predictive analytics capabilities are revolutionizing how businesses make decisions. By analyzing historical data and identifying patterns, AI can forecast future trends, customer behaviors, and market movements with remarkable accuracy. This predictive power is among the most valuable benefits of AI in marketing, as it helps companies anticipate customer needs and optimize their marketing strategies accordingly.

For example, AI can predict which products are likely to sell out during a particular season, allowing businesses to adjust their inventory and marketing campaigns proactively. This data-driven approach reduces risks, improves campaign effectiveness, and ensures that marketing efforts are always aligned with customer demand.

3. Improved Efficiency and Cost Savings

Automating repetitive tasks is another significant benefit of AI in marketing. AI-driven tools can handle time-consuming activities such as data analysis, content creation, email marketing, and social media management, freeing up marketers to focus on strategic initiatives. This automation reduces operational costs, minimizes human errors, and boosts overall productivity.

Chatbots, for instance, are increasingly being used to manage customer service inquiries. These AI-powered bots provide instant responses, resolve common issues, and can even guide customers through the purchase process. By automating these interactions, companies can provide 24/7 customer support without the need for large teams of human agents, resulting in substantial cost savings.

4. Enhanced Ad Targeting and Optimization

AI is reshaping the way businesses approach advertising. With AI, marketers can target their ads more precisely than ever before, reaching the right audience at the right time with the right message. This precision targeting is one of the standout benefits of AI in marketing, allowing businesses to maximize their advertising budget and achieve a higher return on investment (ROI).

AI algorithms analyze user data, such as browsing history, search behavior, and social media activity, to identify the most relevant ads for each individual. This hyper-targeted approach ensures that ads are shown to potential customers who are genuinely interested, reducing ad waste and improving campaign performance.

5. Content Creation and Optimization

Creating engaging content is crucial for any marketing strategy, and AI is making this process more efficient and effective. AI-powered tools can generate content ideas, write blog posts, and even create social media captions based on trending topics and keywords. These tools analyze what type of content performs best with specific audiences, allowing marketers to fine-tune their messaging for maximum impact.

Additionally, AI can optimize content in real time. For example, AI can suggest the best time to post on social media, which keywords to use, and how to structure a blog for better SEO performance. This level of optimization is one of the benefits of AI in marketing that helps brands stay relevant and competitive in a crowded digital landscape.

6. Enhanced Customer Experience with AI-Driven Chatbots

Customer experience is a key differentiator in today’s market, and AI-driven chatbots are elevating how brands interact with their customers. These intelligent bots provide instant support, answer questions, and even make personalized recommendations, creating a seamless customer journey.

AI chatbots can learn from each interaction, improving their responses over time and providing a more human-like experience. This enhancement in customer service not only improves satisfaction but also builds brand loyalty, as customers appreciate the quick and efficient support.

[nenelonomh]

guys,, don't forget to do your research (AI)

researching ai before using it is crucial for several reasons, ensuring that you make informed decisions and use the technology responsibly.

it actually makes me angry that people are too lazy or perhaps ignorant to spend 15ish minutes reading and researching to understand the implications of this new technology (same with people ignorantly using vapes, ugh!). this affects you, your health, the people around you, the environment, society, and has legal implications.

first, understanding the capabilities and limitations of ai helps set realistic expectations. knowing what ai can and cannot do allows you to utilize it effectively without overestimating its potential. for example, if you are using ai as a study tool - you must be aware that it is unable to explain complex concepts in detail. additionally! you must be aware of the effects that it poses on your learning capabilities and how it discourages you from learning with your class/peers/teacher.

second, ai systems often rely on large datasets, which can raise privacy concerns. researching how an ai handles data and what measures are in place to protect your information helps safeguard your privacy.

third, ai algorithms can sometimes exhibit bias due to the data they are trained on. understanding the sources of these biases and how they are addressed can help you choose ai tools that promote fairness and avoid perpetuating discrimination.

fourth, the environmental impact of ai, such as the energy consumption of data centers, is a growing concern. researching the environmental footprint of ai technologies can help you select solutions that are more sustainable and environmentally friendly.

!google and microsoft ai use renewable and efficient energy to power their data centres. ai also powers blue river technology, carbon engineering and xylem (only applying herbicides to weeds, combatting climate change, and water-management systems). (ai magazine)

!training large-scale ai models, especially language models, consumes massive amounts of electricity and water, leading to high carbon emissions and resource depletion. ai data centers consume significant amounts of electricity and produce electronic waste, contributing to environmental degradation. generative ai systems require enormous amounts of fresh water for cooling processors and generating electricity, which can strain water resources. the proliferation of ai servers leads to increased electronic waste, harming natural ecosystems. additionally, ai operations that rely on fossil fuels for electricity production contribute to greenhouse gas emissions and climate change.

fifth, being aware of the ethical implications of ai is important. ensuring that ai tools are used responsibly and ethically helps prevent misuse and protects individuals from potential harm.

finally, researching ai helps you stay informed about best practices and the latest advancements, allowing you to make the most of the technology while minimizing risks. by taking the time to research and understand ai, you can make informed decisions that maximize its benefits while mitigating potential downsides.

impact on critical thinking

ai can both support and hinder critical thinking. on one hand, it provides access to vast amounts of information and tools for analysis, which can enhance decision-making. on the other hand, over-reliance on ai can lead to a decline in human cognitive skills, as people may become less inclined to think critically and solve problems independently.

benefits of using ai in daily life

efficiency and productivity: ai automates repetitive tasks, freeing up time for more complex activities. for example, ai-powered chatbots can handle customer inquiries, allowing human employees to focus on more strategic tasks.

personalization: ai can analyze vast amounts of data to provide personalized recommendations, such as suggesting products based on past purchases or tailoring content to individual preferences.

healthcare advancements: ai is used in diagnostics, treatment planning, and even robotic surgeries, improving patient outcomes and healthcare efficiency.

enhanced decision-making: ai can process large datasets quickly, providing insights that help in making informed decisions in business, finance, and other fields.

convenience: ai-powered virtual assistants like siri and alexa make it easier to manage daily tasks, from setting reminders to controlling smart home devices.

limitations of using ai in daily life

job displacement: automation can lead to job losses in certain sectors, as machines replace human labor.

privacy concerns: ai systems often require large amounts of data, raising concerns about data privacy and security.

bias and fairness: ai algorithms can perpetuate existing biases if they are trained on biased data, leading to unfair or discriminatory outcomes.

dependence on technology: over-reliance on ai can reduce human skills and critical thinking abilities.

high costs: developing and maintaining ai systems can be expensive, which may limit access for smaller businesses or individuals.

further reading

mit horizon, kmpg, ai magazine, bcg, techopedia, technology review, microsoft, science direct-1, science direct-2

my personal standpoint is that people must educate themselves and be mindful of not only what ai they are using, but how they use it. we should not become reliant - we are our own people! balancing the use of ai with human skills and critical thinking is key to harnessing its full potential responsibly.

🫶nene

[probablyasocialecologist]

Once the AI bubble bursts, that doesn’t mean chatbots and image generators will be relegated to the trash bin of history. Rather, there will be a reassessment of where it makes sense to implement them, and if attention moves on too fast, they may be able to do that with minimal pushback. The challenge visual artists and video game workers are already finding with employers making use of generative AI to worsen the labor conditions in their industries may become entrenched, especially if artists fail in their lawsuits against AI companies for training on their work without permission. But it could be far worse than that. Microsoft is already partnering with Palantir to feed generative AI into militaries and intelligence agencies, while governments around the world are looking at how they can implement generative AI to reduce the cost of service delivery, often without effective consideration of the potential harms that can come of relying on tools that are well known to output false information. This is a problem Resisting AI author Dan McQuillan has pointed to as a key reason why we must push back against these technologies. There are already countless examples of algorithmic systems have been used to harm welfare recipients, childcare benefit applicants, immigrants, and other vulnerable groups. We risk a repetition, if not an intensification, of those harmful outcomes. When the AI bubble bursts, investors will lose money, companies will close, and workers will lose jobs. Those developments will be splashed across the front pages of major media organizations and will receive countless hours of public discussion. But it’s those lasting harms that will be harder to immediately recognize, and that could fade as the focus moves on to whatever Silicon Valley places starts pushing as the foundation of its next investment cycle. All the benefits Altman and his fellow AI boosters promised will fade, just as did the promises of the gig economy, the metaverse, the crypto industry, and countless others. But the harmful uses of the technology will stick around, unless concerted action is taken to stop those use cases from lingering long after the bubble bursts.

16 August 2024

[minecraftrelatedrandomness]

So You Want to Get Into Pirates SMP…

Do you enjoy dark fantasy series with intensive worldbuilding? Heart-wrenching character arcs and dynamics? Or do you just like cubitos goofing off or flirting with each other and/or NPCs while going on silly quests looking for treasure? We've got the SMP for you!

Pirates SMP was a whitelist-only, modded roleplay MC SMP hosted by POWCreations (Apokuna and OwengeJuice) in collaboration with noName Ideas, and was run from July 30th to December 10th, 2023.

This post covers an introduction to the worldbuilding, the POV characters, and the main server events. Follow-up posts will cover recommended POVs based on character lore intensity (hard/soft and frequency), how accessible those POVs are, plotline-based recaps, and general fandom resources.

Introduction

Here's the gist of the worldbuilding: the series is set in Ecclesiae Sea, a region surrounded by an extensive wall of ice that won't be discovered until a few weeks into the series. In the heart of the Ecclesiae Sea are the Faction Isles, AKA the Pirate Isles, where the pirates are split into four factions:

Herons: They value exploration and discovery. Some members play the seeker archetype who search for the truth, while others may be explorers, historians, scientists, and/or academics. At their worst, they can be arrogant and a bit snobby, and have been accused of historical revisionism for their own benefit (this is never proven in canon).

Kestrels: They value luxury and are basically the materialistic rich people faction. They like their cash money and appreciate people with the ambition to earn that cash money, and tend to be self-serving. At their worst, they don't care about people around them and can be quite classist, except they make the capitalism funny in the "comically evil" kind of way.

Kites: They value strength in combat and are the type of people to fight god whenever things go wrong. Like the Kestrels, at their worst, they don't care much about the people around them, not even in their own faction.

Nightingales: They value adventure and the friends they make along the way, i.e. they're the found family faction. Most people like the Nightingales, but they are capable of being horrible people at their worst. Some people look down on the Nightingales for being the "softie" faction, and there are jokes about them trauma-bonding over terrible pasts – yes, in canon, and according to cc!Apo, "they're not wrong".

Beyond the Faction Isles, there also exist rogue pirates unaffiliated with any of the four factions, some forming unaffiliated factions of their own, others preferring to sail with their ships and crews alone.

In short, it's Sea of Thieves meets Divergent, except dark fantasy and in Minecraft. The exact nature of the dark fantasy in the worldbuilding (i.e. what series it's similar to in that aspect) is a spoiler for the biggest plot twist in the series, so I won't elaborate on that unless anyone asks/DMs me.

After choosing a faction on their first day, the pirates go on quests to get gold and treasure to upgrade their gear and ships by trading with NPCs. Naturally, there are supernatural evil forces at work that are threatening the pirates' way of life forever, so in the greater server lore, it's their job to figure out what's up. Outside of that, though, many POVs have individual character lore and their own stories to tell.

Annotation: The NPCs mentioned above are usually run on an AI chatbot outside of intensive lore moments, where they would be played by inactive server members or admins. These AI-based interactions play little importance in most plotlines and are generally skippable (as mentioned, actual lore interactions are player-based). However, they are involved in a few unavoidable character dynamics in individual character plotlines. I'll tell you ahead of time whenever these interactions are important.

POV Characters

You might know some of the content creators involved on the server already, so I'm listing them by faction, taking note of their RP character names (if they have one) and pronouns, and when their POVs start because a handful of the POVs start later than Day 1.

Herons (discovery)

OliveSleepy – character pronouns they/them, only appears on Day 1

OwengeJuice – character pronouns he/her and does not use they/them

Scott Smajor – character name Scott Denholm

Snifferish – first appears on Day 52 (Sept 19), only shows up for a couple of streams

SoupForEloise

WaterMunch – character pronouns she/her

ZombieCleo

Kestrels (cash money)

GoodTimesWithScar – only shows up for a couple of streams

Guqqie

ImaShep – character pronouns he/they, first appears on Day 52 (Sept 19)

KyleEff – character name Kyle Foster

Martyn InTheLittleWood – part of V-Tuber lore

MythicalSausage

TheOrionSound – character name Oliver (pronounced "oli-VAIR") von Steel but still goes by Oli

Shubble – first appears on Day 52 (Sept 19), only shows up for a couple of streams

Kites (combat)

Aimsey – character pronouns they/them/any

Bekyamon – character pronouns any/all

CaptainPuffy – only shows up for a couple of streams

Eret – first appears on Day 53 (Sept 20)

Krowfang – character name Kuervo [surname spoiler] but still goes by Krow, character pronouns he/him

Reddoons – only shows up for a couple of streams but makes a couple of non-streaming appearances

Seapeekay – first appears on Day 53 (Sept 20)

Tubbo – only shows up for a couple of streams (streamed regularly before joining the QSMP in mid-August)

Nightingales (found family)

Apokuna – character name [spoiler, currently still unknown] but still goes by Apo, character pronouns he/him

ggAcho – character name Acho (Denholm), character pronouns star/he/they

Graecie

JojoSolos – character name Yoyosephinê but still goes by Jojo, first appears on Day 53 (Sept 20)

Michela DarkEyebrows – first appears on Day 2 (July 31)

Roscumber

WillowMVP – character name Will [surname spoiler], first appears on Day 20 (Aug 18)

Do I have to watch all the POVs to understand the storyline?

For the overall server lore, absolutely not! The event livestreams cover what you need to know:

Day 1 / July 30: The Factioning, or SMP Launch Day

Day 36 / Sept 3: In Too Deep – Chapter 2 starts here; foreshadowing up to this event starts as early as Day 26 (Aug 24) from Scott and Owen POVs, but they recap all the foreshadowing in that day's livestream to get everyone up to speed

Day 76 / Oct 13: The Rescue Mission – foreshadowing up to this event starts as early as Day 59 (Sept 26) from Owen POV, but many of the POVs involved are entwined with foreshadowing, so I'd recommend which POV you should watch for this event on a case-by-case basis; the event is technically skippable as a few people missed this event and had the context recapped to them afterward (i.e. at the next event)

Day 77 / Oct 14: The Revenge Raid – Chapter 3 starts here; occurs directly after Day 76

Day 93 / Oct 30: The Halloween event – this is a NoName event and has very little impact on the greater storyline, and can be skipped in the context of the overall server lore, but is a good watch for individual characterization and lore if you're into that

Day 112 / Nov 18: Final Wishes – Chapter 4 starts here; the plot twist in the event is later adapted into a special lore quest and is completed/revealed in some POVs AFTER Day 112 (since they couldn't make it to the event), and Martyn's Issue 3 of the Noisy Parrot newspaper also gives a summary of the revelations for those unable to complete the quest in time as a second backup option

Day 134 / Dec 10: The Finale

For individual character lore, you can just stick to a main POV and go from there. My recommended watch pattern is picking an individual character POV to go with the server lore all the way through, especially due to how server and individual character lore can often happen in the same livestream, so sticking to a singular POV to start out would give the most context.

For episode-watchers, I highly recommend watching the occasional casual VOD as well, because I've seen a few episode-only fans (for both Martyn and Owen, who currently have the most complete adapted series) say they're feeling a bit lost because they don't understand some of the background lore that contextualizes the situation.

Follow-up Posts

POV recommendations based on character lore intensity

POVs by accessibility

Plotline-by-plotline recap

General SMP resources

[librarycards]

The narrative surrounding AI is that people will be “left behind” unless they adopt it ASAP. How is AI going to revolutionize education? How is it going to transform agriculture? How is it going to make logistics a million times smarter? Almost every sector is being faced with the proposition that they should jump on the AI train or risk getting left behind.

To my frustration, rather than having concerted, critical, and honest conversations around who benefits from this technology—and why and how—we’ve been sold the idea that it’s inevitable, and we better figure out how to make use of it, to deal with it as best we can.

I could see some approaches to AI being more punitive, like “I will do this and this if you use AI” [...] [but] I really wanted to approach my students as empowered agents of their own learning and to express to them, in the best way that I could at the time, what my reservations are. Not just with the tool in a technical sense and how it, as many people have confirmed, is much more like a stochastic parrot than it is something that learns or that is cognitive.

Beyond that, there is the larger “assemblage” of AI that enables these systems to run in the first place. Since I’m an environmental studies professor, it became clear that a lot of those pieces were an entire material world of energy, water, and other resources; of labor undervalued and exploited. And there’s the racialized and encoded assumptions that emanate through the texts upon which these chatbots are trained.

[mariacallous]

The European Union today agreed on the details of the AI Act, a far-reaching set of rules for the people building and using artificial intelligence. It’s a milestone law that, lawmakers hope, will create a blueprint for the rest of the world.

After months of debate about how to regulate companies like OpenAI, lawmakers from the EU’s three branches of government—the Parliament, Council, and Commission—spent more than 36 hours in total thrashing out the new legislation between Wednesday afternoon and Friday evening. Lawmakers were under pressure to strike a deal before the EU parliament election campaign starts in the new year.

“The EU AI Act is a global first,” said European Commission president Ursula von der Leyen on X. “[It is] a unique legal framework for the development of AI you can trust. And for the safety and fundamental rights of people and businesses.”

The law itself is not a world-first; China’s new rules for generative AI went into effect in August. But the EU AI Act is the most sweeping rulebook of its kind for the technology. It includes bans on biometric systems that identify people using sensitive characteristics such as sexual orientation and race, and the indiscriminate scraping of faces from the internet. Lawmakers also agreed that law enforcement should be able to use biometric identification systems in public spaces for certain crimes.

New transparency requirements for all general purpose AI models, like OpenAI's GPT-4, which powers ChatGPT, and stronger rules for “very powerful” models were also included. “The AI Act sets rules for large, powerful AI models, ensuring they do not present systemic risks to the Union,” says Dragos Tudorache, member of the European Parliament and one of two co-rapporteurs leading the negotiations.

Companies that don’t comply with the rules can be fined up to 7 percent of their global turnover. The bans on prohibited AI will take effect in six months, the transparency requirements in 12 months, and the full set of rules in around two years.

Measures designed to make it easier to protect copyright holders from generative AI and require general purpose AI systems to be more transparent about their energy use were also included.

“Europe has positioned itself as a pioneer, understanding the importance of its role as a global standard setter,” said European Commissioner Thierry Breton in a press conference on Friday night.

Over the two years lawmakers have been negotiating the rules agreed today, AI technology and the leading concerns about it have dramatically changed. When the AI Act was conceived in April 2021, policymakers were worried about opaque algorithms deciding who would get a job, be granted refugee status or receive social benefits. By 2022, there were examples that AI was actively harming people. In a Dutch scandal, decisions made by algorithms were linked to families being forcibly separated from their children, while students studying remotely alleged that AI systems discriminated against them based on the color of their skin.

Then, in November 2022, OpenAI released ChatGPT, dramatically shifting the debate. The leap in AI’s flexibility and popularity triggered alarm in some AI experts, who drew hyperbolic comparisons between AI and nuclear weapons.

That discussion manifested in the AI Act negotiations in Brussels in the form of a debate about whether makers of so-called foundation models such as the one behind ChatGPT, like OpenAI and Google, should be considered as the root of potential problems and regulated accordingly—or whether new rules should instead focus on companies using those foundational models to build new AI-powered applications, such as chatbots or image generators.

Representatives of Europe’s generative AI industry expressed caution about regulating foundation models, saying it could hamper innovation among the bloc’s AI startups. ���We cannot regulate an engine devoid of usage,” Arthur Mensch, CEO of French AI company Mistral, said last month. “We don’t regulate the C [programming] language because one can use it to develop malware. Instead, we ban malware.” Mistral’s foundation model 7B would be exempt under the rules agreed today because the company is still in the research and development phase, Carme Artigas, Spain's Secretary of State for Digitalization and Artificial Intelligence, said in the press conference.

The major point of disagreement during the final discussions that ran late into the night twice this week was whether law enforcement should be allowed to use facial recognition or other types of biometrics to identify people either in real time or retrospectively. “Both destroy anonymity in public spaces,” says Daniel Leufer, a senior policy analyst at digital rights group Access Now. Real-time biometric identification can identify a person standing in a train station right now using live security camera feeds, he explains, while “post” or retrospective biometric identification can figure out that the same person also visited the train station, a bank, and a supermarket yesterday, using previously banked images or video.

Leufer said he was disappointed by the “loopholes” for law enforcement that appeared to have been built into the version of the act finalized today.

European regulators’ slow response to the emergence of social media era loomed over discussions. Almost 20 years elapsed between Facebook's launch and the passage of the Digital Services Act—the EU rulebook designed to protect human rights online—taking effect this year. In that time, the bloc was forced to deal with the problems created by US platforms, while being unable to foster their smaller European challengers. “Maybe we could have prevented [the problems] better by earlier regulation,” Brando Benifei, one of two lead negotiators for the European Parliament, told WIRED in July. AI technology is moving fast. But it will still be many years until it’s possible to say whether the AI Act is more successful in containing the downsides of Silicon Valley’s latest export.