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Who's safe kiddos? Glad I don't make a living in Information Technology or work in an office doing any manual input... Interesting now with the way we are going with AI. "LLM" Large Language models will probably wipe out a lot of Data Entry Clerks and Administrators. they are highly susceptible to automation due to repetitive, structured, and unstructured data handling: Customer Service Representatives & Support: Chatbots and AI assistants/agents are managing routine customer inquiries and internal queries. Junior Software Developers & Coders: AI-powered tools are now able to write, debug, and test code, reducing the need for entry-level human developers.
Quality Assurance (QA) Testers: Automated testing tools are becoming more intelligent and faster than manual testers.
Graphic Designers & Content Writers: Generative AI tools (e.g., DALL-E, GPT) can rapidly produce content and designs, lowering demand for entry-level creative work.
Translators and Interpreters: High-level AI language models have rendered traditional translation work largely obsolete.
IT Support/System Administrators: Routine troubleshooting is increasingly handled by AI diagnostics.
I was contracted in the early 2000's by Dell Computers through "Tecnet" --my employer at the time. Dell was based out of Texas and if you reached the call center, there was a person with a strong Texas drawl - similar to the traditional "Deep South" drawl- hard to understand. This soon changed to cost saving remote call centers in India. This arrangement didn't last long at first because people, especially the Texans couldn't understand the East Asian accent. Funny to think but a lot of us couldn't understand either of these parties but the Texans talking to the East Asians is funny to ponder. Call Centers went back to Texas temporarily but then returned to India shortly after. I remember reading somewhere they had training programs for people to lose their accent in Asia call centers.
BB and Reddit: My searches 2026. India Built the World’s Back Offices in mass. A.I. Is Starting to Shrink It. "Artificial intelligence promises to automate the white-collar work that made India a tech powerhouse. The country is racing to adapt before it’s too late."
BB--I'm trying to understand AI myself and help others in laymen's terms!
Linguistic Intelligence is really just the beginning of AI.
What is the Socratic Method of teaching?
Instead of giving information and facts, an instructor using the Socratic method of teaching asks students a series of open-ended questions (questions with more than a yes or no answer) about a specific topic or issue. In turn, the students can also pose questions of their own.
So , I will include the betterment Ideas of LLM instead of the best word inference in the chain that is typical of LLM--
LLM's are so much better when instructed to be socratic.
This idea basically started from Grok, but it has been extremely efficient when used in other models as well, for example in Google's Gemini.
Sometimes it actually leads to a better and deeper understanding of the subject you're discussing about, thus forcing you to think instead to just consume its output.
It works with some simple instructions saved in Gemini's memory. It may feel boring at first, but it will be worth it at the end of the conversation.
Of course AIs do not have critical thinking, but they can trigger and impel their user to activate their own critical thinking capacity. That is the value of a Socratic exchange, it aids the human user in the use of their own, perhaps weak, critical analysis. Over time and repeated use of Socratic exchanges with an LLM, a user will develop greater, better than before, cognitive abilities. I'm not keeping the references to the proof, but this has been demonstrated and published in Psychology journals.
When you tell an LLM to be Socratic, you aren’t magically making it “smarter.” What you’re really doing is reorganizing the interaction loop. Rather than the model collapsing uncertainty into one elegant, finalized response, you’re prompting it to keep the reasoning space open longer. That alters the nature of the conversation.
For example, if you ask Why do startups fail?
a default response might give you a clean list: poor product-market fit, funding issues, bad leadership, etc. It feels complete. But if the model is instructed to be Socratic, it might respond with: Are you asking from the perspective of a founder, investor, or policymaker? or Are you more interested in early-stage failure or scale-stage collapse?
Suddenly, the reasoning space widens before it narrows. The discussion becomes shaped rather than delivered.
LLMs are essentially next-token predictors trained on patterns of conversation and exposition.
By default, they optimize for completion ..they produce something coherent and finished. In Socratic instruction, the objective shifts from answer production to guided exploration. And that shift alone often increases engagement. Consider a student asking, “What is justice?”
A standard response might summarize Rawls, Aristotle, and utilitarianism in a neat paragraph.
A Socratic version might ask: Do you think justice is about fairness, equality, or desert? and Can a system ever produce unequal outcomes?
Now the student has to think. The model hasn’t just transferred information, but it has activated cognition.
Here’s the additional perspective: It’s not only about clearer understanding for the user but also about distributed cognition between human and model.
When the model asks questions back, it externalizes intermediate reasoning steps that would otherwise remain compressed. In a typical answer, much of the reasoning is hidden behind the final synthesis.
In a Socratic exchange, those intermediate steps become interactive checkpoints.
Take a practical case: User: How do I improve my productivity? Default model: gives 10 tips.
Socratic model: What currently distracts you most is digital interruptions, unclear goals, or energy levels?
Now the human provides constraints. The model adapts. The final strategy emerges collaboratively. The intelligence is co-constructed rather than pre-packaged.
So the gain is not merely a feature of the model, it’s a feature of the interaction protocol.
There’s also a cognitive forcing function at work. When models ask clarifying questions, they narrow the hypothesis space and reduce hallucination risk. Instead of guessing what the user means, they query ambiguity directly.
For instance, if a user asks, “Explain the impact of the revolution,” that’s dangerously underspecified. Which revolution? French? Industrial? Digital? A default answer risks misalignment.
A Socratic response might begin: “Which revolution are you referring to, and in what context — political, economic, or technological?” That clarification increases epistemic alignment before any claim is made.
However, there is a tradeoff. Socratic prompting increases depth but reduces throughput. It is inefficient if the task is quick synthesis. If you ask, “What’s the capital of Japan?” a Socratic reply asking, “Are you preparing for a geography exam or planning travel?” is unnecessary friction.
It shines when the task involves: Conceptual learning (e.g., understanding entropy beyond a definition) Moral or philosophical inquiry (e.g., debating free will) Ambiguous problem framing (e.g., defining strategy before execution) Creative exploration (e.g., shaping a novel’s theme through iterative refinement) It is less useful for: Factual lookups Structured output tasks (e.g., “Format this as JSON”) Deterministic problem-solving (e.g., “Solve this equation”)
Socratic prompting does not universally enhance LLM performance. It restructures the reasoning topology of the exchange. It shifts the model from an answer engine to a cognitive scaffold. And perhaps the deeper insight is this: as LLMs grow more capable, the limiting factor increasingly becomes question quality rather than raw model intelligence.
For example, two users can query the same powerful model.
User A asks: Tell me about economics. User B, guided Socratically, refines through dialogue: I’m trying to understand why inflation hurts borrowers differently than lenders — can we unpack that step by step?
The second interaction produces deeper understanding not because the model changed, but because the questioning improved. A Socratic mode doesn’t merely enhance outputs. It upgrades the human participant in the loop. That is why it feels more powerful.
Grok vs ChatGPT are both AI chatbots, but they have different strengths. Grok focuses on real‑time info, quick responses, and a bold, casual tone great for trendy or up‑to‑date queries. ChatGPT offers polished, versatile answers with broad capabilities in writing, reasoning, multimodal content, and professional use. Both tools are useful, it just depends on what you're trying to do.
Learn more: ideacreatezone.com/grok-vs-chatgpt/
#AI #Grok #ChatGPT #ArtificialIntelligence #AIDifference #Tech #AIChat #FutureTech #AIcomparison #grokvschatgpt
Explore the exciting possibilities of the future of AI and its impact on our everyday lives. Discover how Artificial Intelligence technology.
read more : www.astrofree.in/tech/future-of-ai-in-our-daily-life/
247CXchat is arguably the most advanced chat console software available out there for customer contact centres (call centres). It consolidates 8+ customer support channels into one clean interface and maintains all chat & email support history in one view. Brings tons of efficiency and cost savings.
10/09/2024. Team portrait of one of the finalist teams- Policy Summarisation Chatbot attending the Civil Service Data Challenge final event.
Picture by Alecsandra Dragoi / DSIT
A chatbot is not lost on the business world. As brands focus on promoting personalized experiences, more and more intelligent chatbots are being built to engage users and improve brand image. That said it is a rarity to find a live intelligent chatbot, also called as ai based chatbot For several years chatbots were typically customer service environments but are now being used in a variety of other roles within enterprises to improve customer experience and business efficiencies. supportgenie.io/ai-conversational-chatbot/?utm_source=fli...
Fchat.vn cung cấp các dịch vụ cho doanh nghiệp, chẳng hạn như:
+ Trợ lý ảo AI
+ Chatbot Messenger, Zalo, Website
+ Marketing và bán hàng đa kênh
Fchat.vn là một nền tảng trò chuyện trực tuyến và chăm sóc khách hàng toàn diện, giúp doanh nghiệp kết nối và phục vụ khách hàng tốt hơn.
#fchat
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Website: fchat.vn/
Retail companies are using Chatbots to bridge the gap between online and offline experiences. They carry potential to replace the tasks of human workers, like taking customer queries, providing customer service, and upselling to shoppers.
Learn More - www.herbie.ai/industries/retail/
Xác định các từ khóa hoặc cụm từ mà chatbot sẽ nhận dạng và sử dụng để trả lời câu hỏi. Đảm bảo rằng câu trả lời là chính xác và hữu ích cho người dùng.
Xem thêm: bizfly.vn/techblog/crm-la-gi.html
#bizfly #crm #crmlagi
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I tried a random conversation with a chatbot called Myspace Maestro that somebody created in the Meta AI Studio (accessible through the Instagram app). The Myspace Maestro virtual entity is designed to have conversations about "emo" music, fashion, and lifestyle topics.
It was kinda fun. Maybe more fun than having real life friends.
Now we can have virtual friends with virtual images for all of our niche interests and we won't need to interact with real people anymore!
So from here on out, the few of you with whom I interact on Insta, Flickr, or random forums won't have to deal with my sarcasm, snark, or inane questions and idiotic opinions anymore because I'll be hanging out with my virtual friends from now on.
See ya on SpaceHey, m'kay?
(I don't actually have a SpaceHey account... yet... but maybe soon?)
#AIstudio #metaAIstudio #tagsaredeadmandidyoumissthememo