#ChatGPT insights

[marketxcel]

36 Genius ChatGPT Prompts to Help You Prep for Job Interviews

Unlock your potential with 36 brilliant ChatGPT prompts designed to supercharge your job interview preparation. Get ready to impress and excel in your next interview!

[aitalksblog]

Transforming Noisy Investor Reactions into Actionable Financial Insights with ChatGPT

Disclaimer : The information in this post is intended for informational purposes only and should not be considered investment advice. Prior to making any investment decisions, conduct your own research and consult with a financial advisor. (Images generated by author with DALL·E / Bing Image Creator) In the finance world, earnings season is always a busy time for investors. Once those quarterly…

[bowtiedauthor]

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-2/14/25

[glassrunner]

post #839682859 about why i hate generative AI so much, it’s abused to the max by greedy selfish people who are obsessed with consumption rather than creation. all these assholes want is the instant gratification and hollow joy of consuming endlessly, instead of the careful patience and planning of actually making what you want to see

you want fanfic for your ocs? maybe fucking just try writing for once. you want art of them that you’re not willing to commission? pick up a goddamn pencil and learn. stop plagiarizing and stealing and being a soulless content thief just because you don’t know how to cope with a lack of stimulation

[talitha---koum]

If you can get over the seemingly harsh tone of it, and find the underlying tenderness and love, Proverbs is probably your best friend in the world.

[babygirlgiles]

I understand that the person who obviously used chatgpt to comment on my fic probably had their heart in the right place but I genuinely would’ve preferred that they didn’t comment at all. I’ve gotten such a wide variety of comments over the years, from fully fleshed out essays that hit the character limit to wordless key smashes to “beautiful! Thanks for sharing!”. I’ve gotten heart emojis and comments in foreign languages and comments that apologize for not being eloquent or well thought out or any other variation on the theme of “not good enough” because English wasn’t their first language or because they were running late for work or because they’d stayed up until 3am finishing it. And every single time I’ve felt grateful someone took the time to read my work and type a heart emoji into that comment box and press post.

I understand why it’s intimidating to tell someone how much you love their art. I understand why that would feel vulnerable. But I was just vulnerable for 10,000 words so you could read this story. And you can’t be vulnerable long enough to tell me you liked it without using a plagiarism bot?

[omegaphilosophia]

The Philosophy of Ontological Lateness

The philosophy of ontological lateness explores the concept that certain entities or phenomena come into existence or become fully realized only after the preconditions for their existence have been established. This idea can be interpreted in various contexts, such as metaphysics, epistemology, or even existentialism, reflecting on how and why certain aspects of reality or knowledge emerge only under specific circumstances.

Key Concepts in Ontological Lateness

Existential Preconditions:

Ontological lateness suggests that for some entities or concepts to come into being, certain preconditions must first be met. This can relate to the development of complex organisms in biology, the emergence of consciousness in philosophy of mind, or the unfolding of historical events.

Temporal Sequencing:

The notion of lateness implies a temporal sequence where certain phenomena are necessarily preceded by other developments. For instance, advanced scientific theories often rely on foundational discoveries and earlier empirical observations.

Contingency and Necessity:

This philosophy examines the interplay between contingency (things that could have been otherwise) and necessity (things that must be the way they are). It looks at how contingent events and conditions give rise to necessary outcomes in the context of ontological emergence.

Evolutionary Perspectives:

In evolutionary biology, ontological lateness can be seen in the gradual emergence of complex life forms, where each stage of evolution depends on the prior development of simpler forms of life. This gradual process illustrates how complexity and advanced traits appear late in the evolutionary timeline.

Cultural and Historical Development:

Historically and culturally, certain ideas, technologies, and social structures emerge late, building on the foundations laid by previous generations. The Industrial Revolution, for example, was predicated on earlier scientific discoveries and economic conditions.

Examples and Applications

Philosophy of Mind:

Consciousness and higher cognitive functions can be seen as late ontological phenomena, emerging only after the development of complex nervous systems and advanced brains. This perspective highlights how mental states depend on prior physical and biological developments.

Scientific Theories:

Advanced scientific theories, such as quantum mechanics or general relativity, emerged only after significant prior developments in classical mechanics, mathematics, and experimental methods. These theories are ontologically late because they rely on a framework established by earlier discoveries.

Technological Innovations:

Many technological advancements, such as the internet or space travel, could only emerge after the development of fundamental technologies like electricity, telecommunications, and aerospace engineering.

Social and Political Structures:

Democratic political systems and modern legal frameworks are often seen as late ontological developments that depend on earlier societal changes, including the Enlightenment, revolutions, and the establishment of individual rights.

Implications of Ontological Lateness

Understanding Progress:

Ontological lateness provides a framework for understanding the progression of knowledge, technology, and social structures. It emphasizes the importance of foundational developments and the interconnectedness of various stages of progress.

Interdisciplinary Insights:

This philosophy encourages interdisciplinary insights by showing how developments in one field (e.g., biology, technology) rely on prior advancements in other fields. It highlights the cumulative nature of knowledge and progress.

Existential Reflection:

On a more existential level, ontological lateness invites reflection on the human condition, our place in the universe, and the unfolding of individual lives. It suggests that personal and collective growth is a process that builds on previous experiences and conditions.

The philosophy of ontological lateness delves into the nature of existence and emergence, exploring how and why certain entities and phenomena come into being only after specific preconditions are met. By examining the temporal sequencing, contingency, and necessity of ontological emergence, this philosophy provides valuable insights into the progression of knowledge, technology, social structures, and the human experience.

[archidottech]

We're underway with our next round of production so if you are interested in the insights from the industry experts delivering today's technology projects, give us a follow - new articles are dropping soon. Some examples of our previous articles include (links in the comments):

AI, in Reality with Nayur Khan from QuantumBlack, AI by McKinsey Nayur provides industry leading insights into a realistic view of the current state of AI and ethics, looking beyond the hype of ChatGPT and Generative AI https://archi.tech/2023/07/10/ai-in-reality/

Digital Currency with Ricardo Correia from Bain & Company Ricardo is talking about the work that is happening in the background as the global banking system responds to cryptocurrencies and decentralisation, and considers Central Bank Digital Currencies, and the global future of digital money https://archi.tech/2023/11/20/digital-currency-future-of-finance/

IT Mutiny with Richard Stockley from Architecture as a Service Richard is discussing if your IT team undermining how your organisation operates? Are you facing an Agile mutiny? https://archi.tech/2023/04/16/it-mutiny/

Transformation at Scale with Sarah Mcgovern from Manchester University NHS Foundation Trust Sarah is talking about one of the most complex projects we've heard about! What's more, it is a great success story and Sarah has some fabulous insights on how to deliver true transformation projects COMING SOON ........

[theoffingmag]

a lyric essay in one paragraph, repeatedly revised (edits indicated in blue)

I have been teaching my students that humans are storytellers by nature, and then one week I tell them about ChatGPT and artificially generated stories. ChatGPT writes clean prose—no typos, no grammatical errors, no awkward syntax in English—and I have no qualms mocking this text for what it is: a pastiche of natural language, meant to serve whom? I cherish my students. Truly. They write the first layers of stories that they must rewrite, and rewrite, and rewrite, to figure out what it is they really mean, and there is no time, there is no money in the world that shows them what they do is worth something.

Geetha Iyer, "Exquisite Corpus"

[jcmarchi]

How to Realize Value from a GenAI-Enabled Workforce

New Post has been published on https://thedigitalinsider.com/how-to-realize-value-from-a-genai-enabled-workforce/

How to Realize Value from a GenAI-Enabled Workforce

Thanks to OpenAI’s ChatGPT, pretty much everyone knows about GenAI today. Its ability to satisfy people’s thirst for knowledge with just a simple prompt sent it viral. This tool’s usage is truly impressive. It gained a million users in just five days and attracted more than 100 million visitors in its first few months. Individuals and organizations are integrating it into their daily lives and activities with great enthusiasm.

And yet – while GenAI is globally famous, few have moved far beyond experimentation. Organizations are excited by its potential but often struggle to adopt it at a scale that can ultimately create measurable value.

In my role, I’ve been fortunate enough to be able to witness how AI is evolving the way organizations operate and the value it can deliver to customers. Yet, businesses need a guide to turn potential into performance. With these challenges in mind, my team implemented a roll out experimentation with Microsoft’s 350 Copilot, to develop valuable insights and practical strategies for companies aiming to achieve successful adoption and meaningful ROI.

Our path to GenAI value

As we looked into adopting Copilot, our approach helped us identify where its capabilities could add value.

Our experience could be helpful for any organization looking to introduce GenAI into its workflows.

Here are some of the actions that helped us along the way:

Start with a structured adoption framework. For introducing GenAI capabilities, we began by identifying personas in our organization who might benefit from them, and then specific and highly targeted use cases for the technology. Finally, we have created personalized training plans for each role or persona that guide users carefully, so they know exactly how to make the most of the capability.

Use experimentation to validate the technology. For Copilot, we ran an exercise with three groups of users. Group A had no Copilot licenses, while for Group B, we simply gave these users access to the tool, with no training or guidance: it was up to them to work out what to do. Group C got our full adoption framework. The results? We saw a 31% boost in adoption in Group C compared to Group B. Moreover, Group C registered time savings of 2.5 hours per week versus 1.8 hours per week for Group B. The exercise also gave us baseline data, for example on how much time teams could save on specific tasks such as creating presentations. This was another strong example and argument confirming that our adoption framework was working.

Involve employees closely in the process. Exercises like our Copilot experiment help ensure that people engage more readily with new technology. We got people closely involved in selecting the use cases for Copilot, which makes it more relatable, driving adoption and ultimately improving ROI. This process creates evangelists, too. Because our Group C cohort could clearly see the technology’s value for them, they championed it across the company and especially with their teams, encouraging further adoption.

Create hyper-personalized and continuous training plans. We worked with project managers and process owners to make sure that the Copilot use cases were relevant to their everyday tasks, such as producing presentations at very short notice. Armed with this understanding, we created highly tailored training that showed how technology could help them reach their goals. Also, we found that continuous training around creating prompts was very valuable in helping people get the best value out of GenAI. It is also fun and helps keep the community united. For example, we have created a group in which we are sharing useful prompts, and we also have regular short sharing sessions.

Leveraging partners. We tapped our partner to help us by coming in with specific use cases and training offers that helped build our skillsets. In a domain that changes as fast as GenAI, partnership and collaboration are essential to getting good outcomes.

Communicate proactively about employees’ concerns. Questions about ethical AI and whether it will steal people’s jobs are common. It’s therefore important to ensure that the adoption framework clearly defines ethical AI and the ethical use of AI. To ensure responsible and secure use of AI, we leveraged our Responsible AI framework. This framework provides clear guidelines for our employees, aligning with our company values and helping them use AI responsibly. And to allay concerns about GenAI’s impact on jobs, we focused on its ability to take over unpopular mundane and time-pressured tasks such as minute-taking, drafting communications, or sifting through a crowded email inbox. As their proficiency grew, we introduced more sophisticated techniques, including enhancing their ability to create advanced prompts that yield more precise and tailored outputs.

Time, innovation and training

Our experience with Copilot and other GenAI projects is that a structured pilot phase is key, and that people need time to learn the innovative technology. It is also necessary to have a framework for AI adoption and change management that is tailored to your team’s specific needs. Coupled with training and active engagement of users, this will motivate and clear up concerns about GenAI.

Once the technology embeds itself in the organization and spreads out, it becomes part of the culture and accelerates your path to realizing real value from GenAI.

[skores]

ChatGPT told me how to make a Pyramid Scheme.

It might be fiCtiOnAL but seriously, this shit is detailed-

[mehmetyildizmelbourne-blog]

Is SEO Dead or Simply Evolving?

A Strategic Perspective on AI, Content Search, and the Future of Content Marketing Information Management and Knowledge Dissemination While it is difficult to provide a precise count, a simple Google search for “SEO” yields millions of results, indicating the subject’s extensive coverage. This abundance indicates the importance of SEO in digital marketing and the ongoing interest in optimizing…

[justposting1]

How I Became a Data Analyst & Got a Job! (No CS Degree)

Data roadmap I used to learn data analysis and become a healthcare data analyst. In this article, I talk about how I became a data analyst and learned data analytics without a computer science degree. If you are interested in learning data analysis skills and find a data analyst job, watch this video as I go step by step into how I learned data analysis. I was feeling completely lost after…

[topsino]

Meet ChatGPT 4o The Emotionally Aware

[jtem]