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cicerfics · 1 year ago

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Having A Silly Thought about this post:

I think, at some point, Q-branch becomes very absorbed in the discussion of how Evil Overlord and Evil Consort are clearly two separate genders which bear no relationship to the gender binary of masculinity vs. femininity. A cis man can certainly be an Evil Consort! A nonbinary individual or a person whose gender presentation leans more toward the femme side of things can certainly be an Evil Overlord! These things are complex and variable and must not be restricted based on the artificial confines of the gender binary!

There is much discussion on this topic (a very normal topic of conversation in Q-branch, TBH). People begin analyzing themselves to determine whether they are more on the 'Evil Overlord' side of the spectrum or more on the 'Evil Consort' side.

(Soon, a small group insists that a third gender of 'Evil Henchperson' must be created as well, and this is accordingly done. A few other 'evil' genders pop up, too, as some techs choose a different label for themselves. But most people in the department are trying to decide whether they're more of an Evil Overlord or an Evil Consort.)

Graphs and charts are created to analyze the ratio of responses and to sift for patterns in the collected data. (Again, this is a very normal extracurricular activity in Q-branch.)

Q, everyone agrees, is an Evil Overlord and not at all an Evil Consort! This is understood. (Q does not speak to this himself, because he is busy finishing the annual budget, but his minions feel confident that they have assessed him correctly.)

And at some point, 007 turns up in Q-branch and wants to know what's going on with the white board that says 'Evil Overlord' and 'Evil Consort', with tally marks underneath it.

One of the bolder interns explains the matter to him. (Half the techs are now feeling very awkward and avoiding his eyes. How frivolous they must seem to a man who puts his life on the line for England every day!)

But Bond listens very solemnly and then tells them to put a tally mark under 'Evil Consort' on his behalf, because he is UNDOUBTEDLY that type. He is confident that he would look SPLENDID in a skintight black leather outfit, lounging across his overlord's lap while a traitorous minion is brought in for punishment. He would be EXCEPTIONALLY good at climbing out of the water, gleaming and dripping, in a tiny swimsuit, while his Evil Overlord makes evil phone calls on the deck of an evil yacht. He knows EXACTLY what the duties of Evil Consort would entail, and he could perform them with APLOMB. He would bring tremendous style and panache to the role!

...This is probably the point when Q pops out from his office to see what all the ruckus is about, and why Bond is loitering in Q-branch with a bunch of rapt technicians hanging on his every word.

When Bond explains, very seriously, that he is contributing his personal data for use on this important project (he is 100% an Evil Consort, and yes, Carstairs, he WILL fill out your form and offer supplemental data for additional analysis! glad to help!) Q sputters. He tells Bond to stop being ridiculous.

Bond, very seriously, informs Q that he cannot help being so good at smirking, smoldering, and sashaying around in risque outfits. Don't hate the player, Q. Hate the game.

Q is silent for a long, exasperated moment. Then he heaves a sigh and returns to his paperwork.

Meanwhile, the minions nod at each other solemnly, and silently agree that Bond would be an excellent Consort for their beloved Overlord.

...Just another normal day in Q-branch!

#00q #my headcanons #general silliness #james bond #bond will not spend 5 minutes filling out his AARs #but he WILL spend two hours filling out paperwork to support Carstairs' personal research project about the spectrum of evil genders #Q is So Done

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itsbansheebitch · 1 year ago

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More thoughts

I get both sides, but I feel a little confused they couldn't find four people in their +25 employees

Data analyst (Are you seriously telling me you couldn't personally email or even just HIRE matpat's team who do data analytics as part of Theorist Media to help??? The man would be overjoyed to help???)

Editor (Put the first $6 towards a can of coffee grounds, dude)

PR Team (Even, like, a single person, please, for the love of god)

Business Major (Or literally anyone that has taken a home ec/budgeting/personal finance class)

First, the Dish Granted series was started when gold leaf burgers were novel, now it's seen as tone deaf (for obvious reasons) it should have shifted to something like interviews with people who make that kind of food or local businesses (like parmesan cheese shops in Parma, Italy) or the history of food (like talking about the history of modern Native American slavery on Californian wine vinyards). Not to mention the untapped potential of Food Fraud topics. Either shift it, or scrap it. Any data analyst or chronically online person could tell you that.

Second, why did you keep "anyone can afford $6 a month" in? Are the editors asleep at the wheel? Are they overworked? What is going on? You know damn well to not make generalizations about what people can afford. That's NEVER a good idea, especially when you KNOW (because YT gives you analytics) that most of your viewers are young (16/18-30/35 range, I'd guess) who probably, either 1, are still in school and either arent paid well/dont have jobs OR 2, arent paid well and tired of people's shit, like people who own businesses talking about "tough financial decisions." To them, Watcher isn't going to look different from the other people talking like that, because this was so sudden, with no input from fans, and in the video you hear shit like "anyone can afford [X]." To be frank, it wouldn't really matter what the amount is, because that generalization goes against the message they have stood by for years. THAT is a slap in the face.

Third, what are yall doing with the budgeting? Every artist has a right to make art that they are proud of. Every artist deserves to have their work seen if they so choose. Every artist deserves to make a living. HOWEVER, there are MANY options online when it comes to making money, especially on YT. You could get into marketing, data analysis, expanding your demographic, looking at what people are interested in right now VS what will stand the test of time (not gold leaf burgers), etc.

You have to either have these skills, develop these skills, or hire someone to do it for you. It's understandable that you would want a team behind the production, but I find +25 employees to be WAY too many people, especially in LA. Bailey Sarian has a Dark History section on her YT (and Spotify podcast) where she has hired historians to help make sure her episodes are as accurate as possible. You've caught heat before from Puppet History's missing & incorrect info, you should do the same. She has about three (3) "intermissions" per episode for ad breaks. I never see anyone complain. People WOULD listen to yall talk for that long (+1 hour videos), tbh, though that's not necessary.

Why are yall out here with Teslas, expensive food, new gear, scripts (where there weren't scripts before, PH is different, that makes sense), and "better than TV" level sets??? I need to put your accountant in this week's church prayer list what the actual hell??? Ya'll, this video is literally the meme:

Guys help me budget:

LA Rent: 2K per month

Videos: 100K per vid

+25 Employees: God only knows

New stuff for videos: Don't get me started

Like, are you serious?

You have a right to do whatever you want with your art. You have a right to charge whatever you'd like for that art. You have a right to make a living from your art and you have a right to ask your fans for money.

Your fans have a right to be angry when they've been supporting yall for, what, almost 10 years? They have a right to choose when and where to spend their money even when you've made an impact. They have a right to feel betrayed, especially when there are better options (like Nebula or consulting with Theorist Media).

Fans DO NOT have a right to be racist to any members of Watcher, now that they have made a decision they do not agree with.

I personally, think this is a really silly decision and could have been solved (haha solved) with a simple YT poll, but apparently we had to get... this. I respect their decision, I just don't think it was a smart one. I wish them the best, and I hope they find a better solution. Any further comment from me will depend on what steps they take next.

#watcher #shane madej #ryan bergara

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dykealloy · 27 days ago

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the field ecology / zoology field is pretty grim I'm ngl. to lay out all the issues would take a lot of time and more thought than I have the energy for rn but I think to break it down to the main factors: - (1) limited funding (i.e. conservation and capitalism were never meant to mix). The climate crisis and sixth extinction event are cans that politicians keep kicking down the road - government pools their resources towards 'more pressing' concerns. This leads to abysmal pay rates unless you've got many years of research and study behind you (i.e. the academic system has your bank account in a chokehold); - (2) businesses perfectly willing to prey on ethical empathy and passion for the industry (i.e. you should be happy to work extremely hard for us for free because you love animals and the planet and shovelling shit makes you feel good and is a virtuous act of altruism). Which also leads into; - (3) internal hiring structure where sanctuaries and well-known not-for-profits can rely heavily on volunteers and cherry-pick from the people capable of living off their own funding for however long it takes to actually get hired (tbf this issue is exacerbated and arguably caused by factor 1) - (4) dissonance between the politicians and managers who rarely step away from the desk and/or city centre defining environmental regulation and/or standards vs. the people in the middle of fuck-all nowhere (reality) trying to meet those demands or enact that shit (i.e. mathematical optimisation of a model vs. THIS IS NOT A CLOSED SYSTEM IT IS 11PM AT NIGHT I HAVE NO RECEPTION AND I AM BUSH-BASHING THROUGH BLACKTHORN UP A STEEP CLIFF BLINDLY FEELING MY WAY AROUND FOR THIS THREATENED SPECIES so no I was unable to obtain photographic evidence but I can tell you there are historical records of it being here and the habitat is appropriate and I have an audio recording and if you going to tell me this is not enough why the fuck did you bother hiring a zoologist to consult with in the first place) - (5) this could just be my experience in Australia but a lack of mentors / senior ecologists willing or equipped to train fresh blood. There seems to be a massive gap between grunt work (physical labour of being out in the field spotlighting, trapping, etc. and doing hours and hours of mindless data-entry) vs. doing proper analysis, report writing, advocacy and/or the elements of the work that make it feel like you're actually making a difference or progressing in your industry which can causes a lot of disillusionment/dissatisfaction. Leading people to drop out or move on, leading to senior ecologists in small consultancies being stuck with this revolving door or being unable to retain new seniors, then wondering why people move on and complaining about being up to their necks in senior reporting work that they can't offload onto their new staff (whilst also not being able to devote time to training up those staff because they're neck-deep consulting with a government that keeps changing the environmental regulations).

#im still relatively new to the industry but. ugh....#staying in academia is always an OPTION but i hate statistics and office politics and publishing has its own issues......#work woes #zoology #ecology #field ecology #australia #CJ's running mental dialogue

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kanguin · 3 months ago

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Hi, idk who's going to see this post or whatnot, but I had a lot of thoughts on a post I reblogged about AI that started to veer off the specific topic of the post, so I wanted to make my own.

Some background on me: I studied Psychology and Computer Science in college several years ago, with an interdisciplinary minor called Cognitive Science that joined the two with philosophy, linguistics, and multiple other fields. The core concept was to study human thinking and learning and its similarities to computer logic, and thus the courses I took touched frequently on learning algorithms, or "AI". This was of course before it became the successor to bitcoin as the next energy hungry grift, to be clear. Since then I've kept up on the topic, and coincidentally, my partner has gone into freelance data model training and correction. So while I'm not an expert, I have a LOT of thoughts on the current issue of AI.

I'll start off by saying that AI isn't a brand new technology, it, more properly known as learning algorithms, has been around in the linguistics, stats, biotech, and computer science worlds for over a decade or two. However, pre-ChatGPT learning algorithms were ground-up designed tools specialized for individual purposes, trained on a very specific data set, to make it as accurate to one thing as possible. Some time ago, data scientists found out that if you have a large enough data set on one specific kind of information, you can get a learning algorithm to become REALLY good at that one thing by giving it lots of feedback on right vs wrong answers. Right and wrong answers are nearly binary, which is exactly how computers are coded, so by implementing the psychological method of operant conditioning, reward and punishment, you can teach a program how to identify and replicate things with incredible accuracy. That's what makes it a good tool.

And a good tool it was and still is. Reverse image search? Learning algorithm based. Complex relationship analysis between words used in the study of language? Often uses learning algorithms to model relationships. Simulations of extinct animal movements and behaviors? Learning algorithms trained on anatomy and physics. So many features of modern technology and science either implement learning algorithms directly into the function or utilize information obtained with the help of complex computer algorithms.

But a tool in the hand of a craftsman can be a weapon in the hand of a murderer. Facial recognition software, drone targeting systems, multiple features of advanced surveillance tech in the world are learning algorithm trained. And even outside of authoritarian violence, learning algorithms in the hands of get-rich-quick minded Silicon Valley tech bro business majors can be used extremely unethically. All AI art programs that exist right now are trained from illegally sourced art scraped from the web, and ChatGPT (and similar derived models) is trained on millions of unconsenting authors' works, be they professional, academic, or personal writing. To people in countries targeted by the US War Machine and artists the world over, these unethical uses of this technology are a major threat.

Further, it's well known now that AI art and especially ChatGPT are MAJOR power-hogs. This, however, is not inherent to learning algorithms / AI, but is rather a product of the size, runtime, and inefficiency of these models. While I don't know much about the efficiency issues of AI "art" programs, as I haven't used any since the days of "imaginary horses" trended and the software was contained to a university server room with a limited training set, I do know that ChatGPT is internally bloated to all hell. Remember what I said about specialization earlier? ChatGPT throws that out the window. Because they want to market ChatGPT as being able to do anything, the people running the model just cram it with as much as they can get their hands on, and yes, much of that is just scraped from the web without the knowledge or consent of those who have published it. So rather than being really good at one thing, the owners of ChatGPT want it to be infinitely good, infinitely knowledgeable, and infinitely running. So the algorithm is never shut off, it's constantly taking inputs and processing outputs with a neural network of unnecessary size.

Now this part is probably going to be controversial, but I genuinely do not care if you use ChatGPT, in specific use cases. I'll get to why in a moment, but first let me clarify what use cases. It is never ethical to use ChatGPT to write papers or published fiction (be it for profit or not); this is why I also fullstop oppose the use of publicly available gen AI in making "art". I say publicly available because, going back to my statement on specific models made for single project use, lighting, shading, and special effects in many 3D animated productions use specially trained learning algorithms to achieve the complex results seen in the finished production. Famously, the Spider-verse films use a specially trained in-house AI to replicate the exact look of comic book shading, using ethically sources examples to build a training set from the ground up, the unfortunately-now-old-fashioned way. The issue with gen AI in written and visual art is that the publicly available, always online algorithms are unethically designed and unethically run, because the decision makers behind them are not restricted enough by laws in place.

So that actually leads into why I don't give a shit if you use ChatGPT if you're not using it as a plagiarism machine. Fact of the matter is, there is no way ChatGPT is going to crumble until legislation comes into effect that illegalizes and cracks down on its practices. The public, free userbase worldwide is such a drop in the bucket of its serverload compared to the real way ChatGPT stays afloat: licensing its models to businesses with monthly subscriptions. I mean this sincerely, based on what little I can find about ChatGPT's corporate subscription model, THAT is the actual lifeline keeping it running the way it is. Individual visitor traffic worldwide could suddenly stop overnight and wouldn't affect ChatGPT's bottom line. So I don't care if you, I, or anyone else uses the website because until the US or EU governments act to explicitly ban ChatGPT and other gen AI business' shady practices, they are all only going to continue to stick around profit from big business contracts. So long as you do not give them money or sing their praises, you aren't doing any actual harm.

If you do insist on using ChatGPT after everything I've said, here's some advice I've gathered from testing the algorithm to avoid misinformation:

If you feel you must use it as a sounding board for figuring out personal mental or physical health problems like I've seen some people doing when they can't afford actual help, do not approach it conversationally in the first person. Speak in the third person as if you are talking about someone else entirely, and exclusively note factual information on observations, symptoms, and diagnoses. This is because where ChatGPT draws its information from depends on the style of writing provided. If you try to be as dry and clinical as possible, and request links to studies, you should get dry and clinical information in return. This approach also serves to divorce yourself mentally from the information discussed, making it less likely you'll latch onto anything. Speaking casually will likely target unprofessional sources.

Do not ask for citations, ask for links to relevant articles. ChatGPT is capable of generating links to actual websites in its database, but if asked to provide citations, it will replicate the structure of academic citations, and will very likely hallucinate at least one piece of information. It also does not help that these citations also will often be for papers not publicly available and will not include links.

ChatGPT is at its core a language association and logical analysis software, so naturally its best purposes are for analyzing written works for tone, summarizing information, and providing examples of programming. It's partially coded in python, so examples of Python and Java code I've tested come out 100% accurate. Complex Google Sheets formulas however are often finicky, as it often struggles with proper nesting orders of formulas.

Expanding off of that, if you think of the software as an input-output machine, you will get best results. Problems that do not have clear input information or clear solutions, such as open ended questions, will often net inconsistent and errant results.

Commands are better than questions when it comes to asking it to do something. If you think of it like programming, then it will respond like programming most of the time.

Most of all, do not engage it as a person. It's not a person, it's just an algorithm that is trained to mimic speech and is coded to respond in courteous, subservient responses. The less you try and get social interaction out of ChatGPT, the less likely it will be to just make shit up because it sounds right.

Anyway, TL;DR:

AI is just a tool and nothing more at its core. It is not synonymous with its worse uses, and is not going to disappear. Its worst offenders will not fold or change until legislation cracks down on it, and we, the majority users of the internet, are not its primary consumer. Use of AI to substitute art (written and visual) with blended up art of others is abhorrent, but use of a freely available algorithm for personal analyticsl use is relatively harmless so long as you aren't paying them.

We need to urge legislators the world over to crack down on the methods these companies are using to obtain their training data, but at the same time people need to understand that this technology IS useful and both can and has been used for good. I urge people to understand that learning algorithms are not one and the same with theft just because the biggest ones available to the public have widely used theft to cut corners. So long as computers continue to exist, algorithmic problem-solving and generative algorithms are going to continue to exist as they are the logical conclusion of increasingly complex computer systems. Let's just make sure the future of the technology is not defined by the way things are now.

#kanguin original #ai #gen ai #generative algorithms #learning algorithms #llm #large language model #long post

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allaboutkeyingo · 3 months ago

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What is the most awesome Microsoft product? Why?

The “most awesome” Microsoft product depends on your needs, but here are some top contenders and why they stand out:

Top Microsoft Products and Their Awesome Features

1. Microsoft Excel

Why? It’s the ultimate tool for data analysis, automation (with Power Query & VBA), and visualization (Power Pivot, PivotTables).

Game-changer feature: Excel’s Power Query and dynamic arrays revolutionized how users clean and analyze data.

2. Visual Studio Code (VS Code)

Why? A lightweight, free, and extensible code editor loved by developers.

Game-changer feature: Its extensions marketplace (e.g., GitHub Copilot, Docker, Python support) makes it indispensable for devs.

3. Windows Subsystem for Linux (WSL)

Why? Lets you run a full Linux kernel inside Windows—perfect for developers.

Game-changer feature: WSL 2 with GPU acceleration and Docker support bridges the gap between Windows and Linux.

4. Azure (Microsoft Cloud)

Why? A powerhouse for AI, cloud computing, and enterprise solutions.

Game-changer feature: Azure OpenAI Service (GPT-4 integration) and AI-driven analytics make it a leader in cloud tech.

5. Microsoft Power BI

Why? Dominates business intelligence with intuitive dashboards and AI insights.

Game-changer feature: Natural language Q&A lets users ask data questions in plain English.

Honorable Mentions:

GitHub (owned by Microsoft) – The #1 platform for developers.

Microsoft Teams – Revolutionized remote work with deep Office 365 integration.

Xbox Game Pass – Netflix-style gaming with cloud streaming.

Final Verdict?

If you’re a developer, VS Code or WSL is unbeatable. If you’re into data, Excel or Power BI wins. For cutting-edge cloud/AI, Azure is king.

What’s your favorite?

If you need any Microsoft products, such as Windows , Office , Visual Studio, or Server , you can go and get it from our online store keyingo.com

#What is the most awesome Microsoft product? Why?

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sageofsunbloom · 3 months ago

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Is AI fr gonna steal our jobs?

Disclaimer: This post is mostly speculative and meant to encourage discussion and different perspectives on the topic.

Some time ago, I along with many others thought that AI was mostly going to aid in all the task centered, administrative, repetitive jobs. Cashiers, factory workers, call center workers, all the jobs that would benefit from automation were being taken over by AI.

When the ghibli trend came around, it was a guttural shock to many artists.

What used to generate questionable and bad looking art has now developed and is transitioning to generating high quality pieces, videos, music, animation and what not. In a matter of mere months. [AI tools example: midjourney, DALL-E, ChatGPT]

Art is not simply something pretty to look at. It is the accumulation of experiences, emotions and essense of humans. Art is their unique expression and the lens with which they see the world.

This blog is not an argument against the use of AI for art, but a call to understand what it really means.

Did most people see it coming when AI mimicked it with precision?

How long before it starts mimicking creativity, intuition, emotion and depth, all of what we thought was deeply and uniquely human?

"AI works by learning from lots of information, recognizing patterns, and using that knowledge to make decisions or do tasks like a human would." - Chatgpt.

Some time ago, the dominant argument was that AI might be able copy the strokes of a painting, the words of a novel. But it cannot hold the hands of another human and tell them all was well, it cannot feel and experience the real world like us, it cannot connect with humans and it cant innovate and envision new solutions.

If you still believe this, I urge you to go to chatgpt right now and open up to it like it was your friend. It will provide consolidation and advice tailored so well to your individual behaviours that it might feel better than talking to your bestfriend.

What is a deep neurological, experience based and emotional reaction to us is simply just analysis and application of data and patterns to AI. And the difference? Not easily distinguishable to the average human.

As long as the end result is not compromised, it doesnt matter to client and employers whether the process was human or not. Efficiency is often prioritized above substance. And now even substance is being mimicked.

Currently, the prominent discussion online is that in order to improve your job security, we need to master AI tools. Instead of fighting for stability(which is nothing but an illusion now) we need to ride the waves of the new age flooding towards us, and work with Ai instead of fighting against the change.

But the paradox is, the more we use AI the quicker it will learn from us, the quicker it will reduce the need for human guidance and supervision, and the quicker it will replace us.

Times are moving fast. We need everyone to be aware of the rate at which the world is changing and the things that are going on beneath the surface. If we simply take information at face value and avoid research, give it a few years or even months of time, and noone will know what hit us.

"Use of generative AI increased from 33% in 2023 to 71% in 2024. Use of AI by business function for the latest data varied from 36% in IT to 12% in manufacturing. Use of gen AI by business function for the latest data varied from 42% in marketing and sales to 5% in manufacturing."-Mckinsey, Mar 12, 2025.

By 2030, 14% of employees will have been forced to change their career because of- AI-McKinsey.

Since 2000, automation has resulted in 1.7 million manufacturing jobs being lost -BuiltIn

There is a radical change taking momentum right now. It's gonna be humans vs AI starting from the job aspect of the world.

Its not a matter of which jobs and skills are AI proof but which ones is AI likely to take over last.

What I predict personally, is that soon the world leaders are going to have to make a transformative choice.

This can either lead to a world where humans can be provided with money and resources instead of working to earn, as AI generates profit, and we can lay back and enjoy the things we love doing.

Or the other option is that we are going to have to live by scraps as small elite groups take over all the resources and tech.

Dystopia or utopia? The line is blurred.

Thankfully, for now, the choice is in human hands.

#ai generated #awareness #AI awareness #Ai #job security #ai job #ai vs humans #ai discussion #ai artwork #ai automation #rant post #ai speculation #ai blog

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stuarttechnologybob · 10 days ago

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Mobile vs Web vs Desktop, Which Application Development Service Is Right for You?

Application Development Services

Choosing the exemplary Application Development service or professional assistance can be confusing, especially with so many options to choose from—mobile, web, or desktop. Each one has its own benefits, and the right choice depends on your business needs, users, and goals. Let’s explore what each option offers and help you decide which one is the best fit or suits your objective the most.

1. Mobile App Development

Mobile applications are crafted for smartphones and tablets. They run on platforms like iOS/Android operating systems and can be downloaded from app stores for their use as per the demand.

Best for:

Businesses targeting and trying to fetch mobile users

Features and systems inbuild systems like GPS, camera, or push notifications

Real-time user interaction with the app

Pros:

Easy and quick access and get together for users

Better performance and ease of operations on mobile devices

Offline functionality possible within this model

Cons:

Huge costing of building separate or individual apps for iOS and Android

Needs regular updates and upgrades for compatibility

2. Web App Development

Web apps run in browsers and don’t need to be downloaded. They can work and get going for users on both computers and mobile devices as long as internet access is provided or its aligned.

Best for:

Businesses with a broad audience or wide segment users

Apps that don’t need access to device features

Faster and cheaper development

Pros:

Works across all devices

Easier to update and maintain

Lower development costs

Cons:

Need a secured internet connection to function or outperform

Limited or lowered access to mobile hardware features

3. Desktop App Development

Desktop apps get installed directly on a computer, offering more control and power to the user. As these are some of the ideal resources for internal business tools or heavy-duty software.

Best for:

Software that requires high performance

Businesses with specific internal needs

Complex tasks and deliverable like video editing or data analysis

Pros:

Strong performance delivered and speed

Doesn’t always require or demand internet

More secure for enterprise use

Cons:

Limited to desktop users

Requires installation and manual updates

Which Application Development Is Right for You?

If your target users are always on mobile devices, consider developing a mobile app. If you want something easy to access and update, choose web development. For feature-rich, high-performance apps, desktop development is a wise choice.

Professional companies like Suma Soft, IBM, and Cyntexa can guide you through the Application Development process and help you pick the right path based on your goals. Making the correct choice today ensures better results tomorrow.

#app development #application development #itsolutions #it services #technology #saas #software #saas development company #saas technology #digital transformation #usa

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cloudvision14 · 12 days ago

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Mastering AI-Based - Competitor Report & Ad Strategies

In the modern digital battlefield, brands are not just competing with direct rivals—they’re competing for attention, relevance, and customer loyalty in a crowded, fast-moving landscape. With the surge of marketing channels, evolving consumer behavior, and unpredictable algorithm shifts, understanding what your competitors are doing has become more important than ever. Enter the age of AI-powered intelligence, where marketers no longer need to rely on guesswork or outdated reports. Today, AI-Based - Competitor Report & Ad Strategies are transforming how businesses decode their competition and outsmart them with data-driven precision.

Why Does Competitor Intelligence Matter?

Before diving into how AI enhances competitor analysis, it’s essential to understand its value. Competitor intelligence helps businesses:

Identify market trends early

Spot gaps in their own strategy

Benchmark performance metrics

Discover winning ad creatives and formats

Refine pricing, messaging, and targeting

Without structured intelligence, you’re effectively navigating in the dark. But with the right tools, you can gain a panoramic view of your industry, fine-tune your marketing, and confidently invest in strategies with higher ROI.

Traditional Methods vs. AI-Powered Approaches

Traditional competitor research often involved manual tracking, surveys, reviewing public content, or using isolated data from SEO and social tools. While useful, these approaches are slow, limited, and reactive.

AI-powered competitor analysis, on the other hand, uses machine learning and automation to track thousands of data points across websites, ad copy, social platforms, and customer reviews—all in real time.

For example, instead of merely noting that a competitor is running ads on Facebook, AI tools can show you:

The ad creatives used

Duration and frequency of campaigns

Audience engagement metrics

Landing page performance

Budget estimates and targeting styles

Key Features Of AI-Driven Competitor Tools

Most advanced platforms offering AI-Based - Competitor Report & Ad Strategies come packed with features that go beyond basic comparisons. Some of the most valuable capabilities include:

Ad Creative Library

Access a visual archive of ad creatives your competitors are running across platforms like Facebook, Instagram, YouTube, and Google Display.

Targeting Insight

See which audience demographics, locations, and interests are being targeted, helping you refine your own segmentation strategy.

Engagement & Performance Metrics

Understand which ads are getting the most clicks, shares, and conversions—allowing you to model what works.

Trend Detection

Identify emerging trends in copywriting, visuals, formats, and placement.

Benchmarking

Compare your own performance against top competitors on metrics like click-through rate, CPC, and ad frequency.

Best Practices For Using AI-Based Insights

Having powerful data at your fingertips is just the beginning. AI at Work means mastering how to interpret competitor reports and translate insights into strategic, data-driven decisions:

Don’t Copy—Adapt: The goal isn’t to mimic your competitors but to understand what works and customize it for your unique brand voice and goals.

Focus on Patterns: One ad may go viral by chance, but consistent performance reveals reliable tactics. Look for patterns in creatives, timing, and audience response.

Combine with Internal Data: Match competitor insights with your own campaign data to refine A/B testing and predictive modeling.

Act Quickly: The value of real-time insights lies in speed. If you see a new offer or message gaining traction, test your own version immediately.

Use Multi-Platform Intelligence: Competitor behavior varies across platforms. Use tools that integrate data from multiple sources for a holistic strategy.

The Future Of Competitive Strategy Is AI-Powered

As markets grow more competitive and data becomes more abundant, businesses that don’t leverage AI will struggle to keep up. The ability to observe, learn, and act—powered by automation—is the new marketing edge.

Platforms offering AI-Based - Competitor Report & Ad Strategies are no longer optional; they are essential tools for staying ahead. Whether you're a startup aiming to disrupt your industry or an established brand defending your market share, AI can be your strategic partner in decoding what the competition is doing—and doing it better.

You can also watch: Globussoft: The Future of AI-Powered Business Starts Here!

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Conclusion

Mastering competitive intelligence isn’t just about tracking your rivals—it’s about understanding the “why” behind their actions and using those insights to make smarter moves. Thanks to AI, this process is faster, more accurate, and more impactful than ever before.

FAQs

1. What is an AI-based competitor report?

It’s a report using AI to track competitors’ ads, strategies, and audience insights, helping you make smarter, data-driven marketing decisions.

2. How accurate are AI tools in tracking competitor ads?

AI tools offer real-time, reliable data by analyzing ad creatives, engagement, and targeting from multiple platforms for accurate competitor insights.

3. Can small businesses benefit from AI-Based - Competitor Report & Ad Strategies?

Yes, small businesses can use AI tools to gain insights, optimize marketing efforts, and compete effectively without needing a large advertising budget.

#marketingstrategies #competitoranalysisseo #competitoranalysistools #competitoranalysis #competitorresearch #Youtube

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sagetitansteam · 4 days ago

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Is the Marketing Funnel Dead? Rethinking Customer Journeys as Spirals, Not Straight Lines?

The Evolution Beyond Linear Thinking

From Funnels to Flywheels: A Paradigm Shift

The inflexible architecture of conventional funnels presumes customers progress in a linear fashion from awareness to consideration to buy. But this is far too neat a picture for today's reality. Today's customers research, compare, abandon, return, and sometimes become evangelists before even making their first purchase. This is where flywheel marketing steps in.

What does a flywheel mean in business? Flywheels, on the other hand, show continual momentum, while funnels terminate with conversion. The flywheel marketing approach knows that happy consumers are the best way to get new customers, which starts a cycle of growth that keeps going. Customers that have great experiences automatically tell their friends about you, leave reviews, and buy from you again, all of which help your business expand.

Understanding Modern Consumer Behavior

Today's consumers operate in micro-moments—brief instances when they turn to devices to act on a need. These moments don't follow funnel logic. A customer might discover your brand through social media, research competitors on their laptop, read reviews on their phone, and finally purchase weeks later through a completely different channel.

Behavior-based marketing acknowledges these complex patterns. Behavioral marketing study shows that customers often go back to the same information over and over, look for confirmation from friends, and make choices based on things that have nothing to do with your original marketing message. Understanding consumer behavior in marketing strategy means accepting this non-linear reality.

The Rise of Intent-Driven Marketing

Responding to Behavioral Triggers

Modern marketing success depends on recognizing and responding to behavioral triggers in marketing cloud platforms. These triggers indicate where customers are in their unique journey, regardless of traditional funnel stages. Behavior in digital marketing is about reading these signals and providing relevant experiences at precisely the right moment.

Intent-driven marketing goes beyond demographic targeting to focus on what customers are actually doing. Are they comparing prices? Reading reviews? Downloading resources? Each action represents an opportunity to provide value, even if it doesn't immediately lead to conversion.

The Power of Data-Driven Insights

The benefits of data driven marketing become apparent when you stop forcing customers into funnel stages and start understanding their actual behavior patterns. Advanced analytics reveal the true customer journey—often resembling a spiral more than a straight line. Customers circle back, influence others, and create value long after their initial purchase.

Mapping the Modern Customer Journey

Understanding Every Touchpoint

Touchpoint research shows how complicated modern client journeys are. A touchpoint in marketing is more than simply an ad or an email. It's every time a customer interacts with your brand, like when they talk about it on social media or phone customer care. Touchpoint analytics can show you which encounters really affect decisions and where customers might be leaving or becoming lost.

Think about this: a customer might first hear about your brand through a podcast ad (upper funnel marketing), then look up your competitors on Google, read reviews on other sites, visit your website several times, interact with your social media content, and finally buy something through a retargeted ad (lower funnel vs. upper funnel marketing shows how complicated this journey is).

Implementing Omnichannel Excellence

Omnichannel marketing strategy is necessary when customers don't have linear journeys. Your message should be aligned and relevant on all channels, but customized to fit each platform's specific context. This is not about being everywhere—it's about being everywhere your customers are naturally present.

Full-funnel marketing evolves to mean something different: instead of pushing customers through stages, you're creating value at every potential interaction point. Full funnel marketing b2b requires understanding that business buyers often involve multiple stakeholders, each with different information needs and decision-making timelines.

The Inbound Marketing Evolution

From Interruption to Attraction

The inbound marketing evolution perfectly illustrates this shift from linear thinking to spiral engagement. Early inbound marketing examples focused on attracting visitors, converting them to leads, and nurturing them to customers. The inbound marketing process has evolved to recognize that advocacy and delight phases create new attraction opportunities.

Content marketing evolution reflects this change. Rather than developing content for individual funnel stages, successful brands develop valuable assets that serve customers along the entire relationship. A single asset can both educate prospects, serve current customers, and offer shareable value to advocates.

Practical Implementation Strategies

Building Your Flywheel Approach

First, figure out where your customers now interact with you and then sketch out their real routes instead of the ones you think they take. Look for patterns in behavioral marketing research data. For example, where do customers usually interact with your brand more than once? What actions predict eventual conversion or advocacy?

Set up behavioral triggers that respond to customer behaviors instead of random deadlines to use intent-driven marketing. Have meaningful follow-up ready for when someone downloads a resource, views pricing pages, or interacts with support content. This follow-up should add value instead of merely trying to get them to convert.

At Sage Titans, we've seen how this spiral approach transforms customer relationships from transactional interactions into ongoing partnerships that generate sustainable growth.

The Future of Customer Engagement

The marketing funnel isn't gone; it's changed. Today's customer journeys look like spirals, with customers coming and going from interaction, affecting others, and adding value in ways that traditional funnels never saw coming. To be successful, you need to accept this complexity and create marketing tools that help clients no matter where they are in their own path.

Businesses may build long-lasting growth engines that depend on customer satisfaction instead of merely getting more customers by adopting flywheel marketing principles, focusing on behavioral triggers, and making sure that all touchpoints are of the highest quality. Brands that see customer journeys as ongoing partnerships, not linear procedures with set endpoints, will be successful in the future.The companies that recognize this shift and adapt their strategies accordingly won't just survive the evolution of customer behavior—they'll lead it. At www.sagetitans.com, we help businesses make this transition from funnel thinking to flywheel success, creating marketing systems that grow stronger with every satisfied customer.

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erik-even-wordier · 5 months ago

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A word on the "move fast and break things" concept

A word on the "move fast and break things" concept. It comes from tech, as you probably know, and was very much the Amazon ethos. And I'm actually a fan of it, when it's deployed correctly. But it's now being used to justify malicious people doing reckless things in the stupidest ways possible, and that makes me mad.

So if someone in your life is under the delusion that Pres. Musk and his band of bros are just being "entrepreneurial" or "operating at internet speed" or whatever and the outcome will be glittering success, here's what "move fast and break things" is SUPPOSED to mean:

* Design and code products and features in an iterative way so that you can respond to customer/market needs quickly, vs taking forever to build something that might not even be relevant anymore once you're done. Launch something, get feedback, tweak or add to it, get more feedback, etc. This can be tricky to get right--we've probably all seen the definition of "minimum viable product" stretched to within an inch of its life at times--but I think it's a net good for companies and consumers alike.

* Understand when you have ENOUGH information to move forward responsibly, even if you might LIKE to have a little more. Analysis paralysis is real. (I can personally attest to this as one prone to it.) Certainty is seductive. But endless dithering over edge cases and what-ifs means no forward momentum. This also applies to over-reliance on consensus. You need your key stakeholders on board with your plan, but waiting for universal approval is a route to getting nothing done. When people ask how I succeeded for twelve years at Amazon, a company the average (and saner) employee leaves within eighteen months, my answer is that I learned how to navigate and even thrive in ambiguity, so that I could make decisions in fast-changing circumstances and take measured risks.

* Distinguish between one-way and two-way doors. Two-way doors are decisions that can readily be reversed if it turns out that when you moved fast, you broke something important. One-way doors are permanent, and a sign to slow way down. When I took those "measured risks," I mean I was also aware of when making a mistake would mean real damage to customers or the business--and thus potentially also to my own reputation--and proceeded much more cautiously.

Here's what it's NOT supposed to mean:

* Recklessness with foundational systems. For one thing, remember that it's a TECH maxim, meant to apply mostly to digital environments where code is easily deployed and rolled back. One of the teams I led at Amazon experimented with different kinds of email subject lines. If one of them had disastrous open rates, we could just pull it (or the algorithm would pull it for us). Yeah, it meant that tens of thousands of customers had received a mail from us that they didn't find useful. That's not great, because once you've trained a customer to ignore or even unsubscribe to your emails, it's really hard to get their attention back. But that was the price of learning. And it didn't HARM customers, or break their trust. And even in a tech environment, we would never EVER have played it fast and loose with, say, the system for storing customer data or managing employee benefits. The stakes are way too high, just as they might be with, say, safeguarding the nuclear stockpiles of the United States of America.

* Failure to plan. Even when you know you might break things, you try to anticipate those things in advance and have a mitigation plan. At Amazon we even tried to anticipate "dogs not barking," our phrase for unintended consequences that happen below the radar and so go unnoticed for too long. Did DOGE take the time to either ensure it wasn't firing HUNDREDS of mission-critical people or to have a fast rollback plan? Apparently not. (The nuclear scientists' email accounts were wiped as soon as they were fired, forcing HR to hunt people down one by one via personal accounts.) I also wouldn't consider these firings a two-way door. Even if your people come back to work, the experience of being fired (illegally, let's not forget) by a ketamine-addled billionaire who is ALSO operating illegally--and who the White House claims is neither the DOGE director nor a DOGE employee--won't fade anytime soon. The chaos and breach of trust are irreparable.

* Lack of coordination. Even in a rambunctious tech environment, teams did not take it well when some other team's code changes broke their stuff without plenty of advance warning. That's amateur hour, not to mention assholery. Before you fire the one locksmith for all of Yellowstone, maybe you give his boss a heads up and time to arrange coverage.

To be clear, I don't think Elon Musk and his band of young bros are TRYING to "move fast and break things" in the right way. Their goal is to destroy the federal government, not improve it, so they don't think they need to take any care. (Which is the Achilles heel of the whole Trump administration; instead of taking the time to ruin things in a legally defensible way, they proceed with all the finesse of thugs using Adderall as chaw and get smacked down in court, again and again.)

But they ARE banking on the public being dumb enough to believe that this is just how the wealthy, successful, super-ultra-modern tech class got that way. It's not true. So don't fall for it.

PS: also, THE GOVERNMENT IS NOT A BUSINESS AND SHOULD NOT BE RUN LIKE ONE. Would I like our government to be more agile and efficient? Absolutely. I think we all would. But a large bureaucracy will NEVER run like a corporation, and that’s not just inevitable, but desirable in some ways. Institutions are MEANT to be stable and predictable.

#shared from facebook #doge #move fast and break things

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smitharticle · 2 months ago

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Analyze Backlinks and Referring Domains

Backlinks vs Referring Domains

Search engine optimization (SEO) centers on building authority and trust. One of the most significant and confusing parts of SEO is backlinks versus referring domains. These two terms are frequently intermixed, but each acts as a unique contributing factor to your website rankings. Understanding the difference and knowing how to analyze and optimize for both can give your SEO much more value.

What Are Backlinks?

A backlink is simply a link from another website to your website. When a search engine sees a link to your content by another site, this is an indication that other people find your content valuable or useful. The more quality backlinks you have, the higher your site will rank for high-quality keywords.

But it's not about quantity; it's about quality. One link from a good and authoritative site is worth ten times the worth of numerous low-authority links or links from mostly unrelated sites.

What Are Referring Domains?

Referring domains are the unique websites from which your backlinks originate. For example, if you receive 10 backlinks from the same website, it still counts as one referring domain. Google and other search engines consider referring domains an important ranking factor because they show how many different sites trust your content.

Why Seobix Is the Right SEO Tool for Link Analysis

Seobix is a backlink checker and an SEO optimizer tool that has a strong yet simple interface, and when you analyze other backlink checkers and SEO optimizer tools, you will find that Seobix has superior analytics features to show both referring domains vs backlinks, and that will help you with making data-driven decisions. We welcome all users who are online studying free SEO tools as a beginner, and professionals who are consistently seeking the best SEO tools.

Final Thoughts

Knowing the distinction between backlinks and referring domains is not merely a nitty-gritty detail—it's an SEO rule that can break or make you. Backlinks tell you about frequency of mentions on your site, while referring domains tell you about how many original sources are referencing you.

To excel at SEO, you need quality and variety. And with a cutting-edge SEO tool such as Seobix, it is easy to track, analyze, and improve both quality and variety. To business owners, bloggers, or marketers, having the necessary tools places you at the top to remain in front of competition in search results.

Begin using Seobix today and see how simple and powerful SEO optimization is.

#digital marketing #seo tools #seo optimized #backlinks

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xpressluna · 3 months ago

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I Hate Seeing Writers Not Making MoneySo Here Are 8 Ways to Make More as a Writer

Here’s the truth: great writing alone doesn’t guarantee great income.

I’ve seen too many talented writers underpaid, undervalued, or stuck in passion projects that don’t pay the bills. And it frustrates me — because writing is a skill that’s in demand everywhere. You just need to know how to position it, sell it, and scale it.

If you're ready to stop writing for exposure and start earning what you're worth, here are 8 practical, proven ways to make more money as a writer.

Freelance for High-Paying Clients (Not Content Mills)

You don’t need to accept \$20 blog posts when there are companies and entrepreneurs willing to pay \$300–\$1,000+ per article. The secret is targeting niches that need content to drive business, like:

SaaS and tech

Personal finance

Healthcare

B2B services

Pitch directly, build a niche portfolio, and learn how to charge by value, not word count.

✅ Pro Tip: Start by rewriting your services to focus on outcomes — like “I help SaaS brands attract customers with SEO content” vs. “I write blog posts.”

Offer Ghostwriting Services

Ghostwriting is one of the highest-paying forms of writing — and most clients don’t care about you getting credit; they care about results. You can ghostwrite:

LinkedIn thought leadership

Executive blogs

Nonfiction books

Email newsletters

It’s creative, lucrative, and repeatable.

✅ Rates: Ghostwritten LinkedIn posts can earn \$200–\$500/post. Books? Thousands.

Sell Digital Products

Turn your knowledge into scalable income with digital products like:

Ebooks

Notion templates

Writing guides

Pitching scripts

Once created, they can sell indefinitely with no ongoing labor. Perfect for writers with an audience or niche expertise.

✅ Tools: Use Gumroad, Payhip, or Podia to start selling fast.

Start a Paid Newsletter

If you love writing essays, storytelling, or niche commentary, why not monetize it with a paid newsletter? Services like Substack or Beehiiv let you build free + paid tiers.

You don’t need 10,000 subscribers — just 100 people paying \$5/month = \$6,000/year in recurring income.

✅ Best Niches: Personal finance, creator economy, niche analysis, industry trends.

Teach What You Know (Courses & Workshops)

Writers often forget — the way you write, think, and communicate is a teachable skill.

Package it into:

Online courses (e.g., “How to Write Better Cold Emails”)

Cohort-based workshops

Private coaching for new writers or business owners

✅ Platforms: Teachable, Circle, Maven, or even Zoom + Stripe to start.

Monetize with Affiliate Writing

If you write product-based content or reviews, affiliate marketing is a great passive income stream. You write once, and earn commissions every time someone buys through your link.

Best niches: Software, writing tools, education products, lifestyle gear.

✅ Pro Tip: Focus on high-ticket or recurring commissions (like SaaS tools).

License Your Writing

You can earn money by licensing your existing content to brands, newsletters, or websites. If you’ve written a high-performing article, offer a non-exclusive license to republish it for a fee.

Also consider:

Licensing quotes or content to marketers

Offering a “writing bundle” to creators or agencies

✅ This works well for evergreen, data-driven, or inspirational content.

Write for Yourself — Then Monetize It

Blogging, storytelling, or journaling can become income if you build a brand around it. Writers like Morgan Housel and Anne-Laure Le Cunff built huge audiences through consistent, personal writing — then monetized with books, speaking, courses, and sponsorships.

✅ Just start: Build your platform. Even 1,000 loyal readers can turn into six figures over time.

Final Thoughts

Writing is not a dead-end job. It's a high-leverage skill that can create freedom, income, and impact — if you treat it like a business.

If you’re a talented writer struggling to make money, it’s not a lack of skill. It’s usually a lack of strategy.

Pick one or two methods from this list. Go deep. Get paid.

And never again write “just for exposure.”

#trending #art trend #viral trends #3d printing

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