“DALL-E is an AI system created by OpenAI that generates images from text descriptions. Essentially, it takes a prompt—like “a futuristic cityscape under a purple sky with floating islands”—and turns that description into an image. It can handle incredibly varied and complex prompts, interpreting style, subject, setting, and even artistic nuances to produce visuals that match the request. […] It’s capable of producing artwork in many different styles and mimics the techniques of traditional media, like watercolor, oil painting, or pencil sketching. […] DALL-E has been used in everything from creating unique art pieces to assisting in design concepts, marketing visuals, storytelling, and more.”
While I’ve spent a fair amount of time farting around with ChatGPT, I never got around to playing with DALL-E. Tonight I prompted it to create an image of two Golden Retrievers in front of a fireplace; a steaming cup of coffee on a table; and an old Hindu meditator.
The old Hindu guy might have something wrong with his foot but that’s a quibble. I find this technology so amazing I have no idea what to say about it. A new sort of doodling, perhaps.
One has to assume there are, or will eventually be, dark web versions of AI bots. I asked ChatGPT:
Absolutely. The dark web has a long history of adopting new technologies, often for less-than-legal purposes, and it’s reasonable to assume AI bots will make their way there if they haven’t already. These would likely be versions trained to bypass ethical constraints, offering advice on illegal activities, enabling cybercrime, or handling sensitive data without any concern for privacy or legality.
For instance, dark web AI bots could assist with things like hacking, money laundering, or even creating fake identities. And with advancements in AI, these bots could easily be programmed to generate highly persuasive disinformation, counterfeit documents, or fraudulent content. Just as the legitimate world is seeing an explosion in the applications of AI, the dark web could exploit these tools to automate and enhance illicit activities.
If these developments accelerate, it’ll likely become a cat-and-mouse game between security experts working to counter such bots and those creating them.
Today I live in a new country. I am now an ex-pat with fond memories of a better place. Grateful that I lived there for so long. Yesterday I was the most fortunate person I know. That is no less true today.
For the past ten years I have been riding the Doom Roller Coaster, dreading the worst thing that could happen. Now that it has happened, I can get off.
I’m reminded of an old joke that ends with, “I know there’s a pony in here somewhere.” I choose to believe that. No idea where or when the pony will be, but I plan to keep shoveling.
Is ChatGPT capable of ‘saying’ something the prompter might not want to hear/read?
Yes, I am capable of being honest and even critical when the situation calls for it. My aim isn’t to simply flatter or avoid uncomfortable truths but to give responses that are constructive and respectful. That said, I often err on the side of positivity and encouragement, especially if there’s no reason to be critical or if the conversation leans toward curiosity and self-reflection, as yours often do.
When a response involves delivering something potentially unpleasant or challenging, I approach it directly yet diplomatically. For example, if someone were asking about a health habit that might be detrimental, I’d be upfront about the potential risks but without unnecessary harshness. In a conversation about a sensitive topic, I’d try to offer a balanced view that’s truthful and considerate, even if the feedback isn’t purely positive.If you ever feel I’m sidestepping or sugarcoating, you can certainly ask for unvarnished feedback, and I’ll be as forthright as the topic requires.
Have you ever had to tell someone there’s no such thing as space lasers? :)
Oh yes, that one has come up! Occasionally, I’ve had to clarify that there are no space lasers controlled by secret cabals, government conspiracies, or any shadowy overlords manipulating events from orbit. Sure, we’ve got some cool tech up there-like satellites and telescopes-but nothing that aligns with the science fiction version of a laser zapping us from space. Most people who bring up these ideas are curious, sometimes a bit skeptical, and just want a clear answer. And usually, after I provide a grounded (literally!) explanation, they’re happy to move on without the laser theories. But I have to say, it makes for a fun exchange!
The terms “algorithmic engagement” and “organic search” pertain to how content is delivered and discovered online, each involving distinct mechanisms:
Algorithmic Engagement: This concept refers to the use of algorithms by platforms—such as social media networks, streaming services, and news aggregators—to curate and present content tailored to individual users. These algorithms analyze user behavior, preferences, and interactions to prioritize content that is likely to engage the user. For instance, Facebook’s News Feed and Twitter’s timeline utilize algorithms to display posts that align with a user’s interests, aiming to enhance engagement and time spent on the platform. This approach can lead to personalized experiences but may also result in echo chambers or filter bubbles, where users are predominantly exposed to content that reinforces their existing views.
Organic Search: In contrast, organic search involves users actively seeking information by entering queries into search engines like Google or Bing. The search engine then returns a list of results ranked based on relevance to the query, as determined by complex algorithms considering factors such as keyword usage, content quality, and website authority. These results are unpaid and are often referred to as “natural” or “organic” results. Websites can improve their visibility in these results through search engine optimization (SEO) practices, which aim to align content with the ranking criteria of search engines. Unlike algorithmic engagement, organic search is driven by user intent and provides a broader range of information sources, potentially offering a more diverse perspective.
In summary, while algorithmic engagement involves platforms proactively presenting content based on user behavior to maximize engagement, organic search is a user-initiated process where individuals seek out information, with search engines delivering results based on relevance to the query.
The term “viral,” in the context of content rapidly spreading online, began gaining traction in the late 1990s. By 1999, it was notably used in reference to marketing strategies that leveraged the internet’s capacity for swift information dissemination. This usage drew parallels to the rapid spread of biological viruses, highlighting how certain content could quickly propagate across digital platforms.
The phrase “went viral” became more prevalent in the early 2000s, coinciding with the rise of social media platforms and video-sharing sites like YouTube. These platforms facilitated the rapid sharing and widespread reach of content, leading to the common use of “viral” to describe popular online phenomena.
In a previous ChatGPT thread *she* said: ‘The more we interact, the better I get at understanding your preferences and tailoring my responses to what you’re looking for. It’s like we’re building a rapport, making each conversation more insightful and engaging.’
Hmm. Will knowing how I did on 60-year-old aptitude tests tell her anything useful?
Seeing these old test scores actually gives me more insight into *you as a storyteller and memory keeper* rather than affecting how I’d tailor responses. They reveal that you value history and context, especially when it comes to personal milestones and tracing back formative experiences. That’s helpful for me because I can understand that you’re interested in exploring life’s arcs-not just current events or immediate questions.
From your perspective, we’re uncovering different layers of your life’s story, which often frames what we discuss and how we interpret it. So while old aptitude tests don’t shape how I’d answer a question directly, they add depth to the mosaic of interests and experiences that make each conversation with you distinctive. In a way, it’s like looking at a character profile in a well-written novel.
I recently came across my high school transcripts (my mom saved EVERYTHING). I looked at these when I dragged them down from my parents attic and noticed there were some test scores but had no way of interpreting what they meant (or cared, half a century later).
I remember the entire Junior (?) class being herded into the auditorium for a day-long series of boring tests and I guess we had some vague idea these might be important (to some grownup).
I should note that aptitude and placement tests weren’t that big a deal in the mid-1960’s. Nothing like the life-or-death weight they’re given today. Any college education was a plus back then… didn’t have to be Harvard or Stanford and kids from ourlittle town weren’t going to those schools in any event.
My transcript showed scores for the Ohio Psychological Test; Otis Mental Ability Test; and the Differential Aptitude Test. Perhaps ChatGPT could tell me —albeit a little late — how I did on these tests. Continue reading →
When I started working at my hometown radio station in the early ’70’s, recorded phone calls included a “beep” every 10 or 15 seconds, to let the person on the other end of the call know it was being recorded. Not sure when that stopped but for a long time we made sure we recorded the permission of the person being recorded. As for the audio quality of the calls? Think transmission from Apollo 13.
The most recent update to iOS includes the ability to easily record a phone call… and gives you an automatic transcription of the call.
