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#chatbots

17 posts16 participants0 posts today

"For the past two and a half years the feature I’ve most wanted from LLMs is the ability to take on search-based research tasks on my behalf. We saw the first glimpses of this back in early 2023, with Perplexity (first launched December 2022, first prompt leak in January 2023) and then the GPT-4 powered Microsoft Bing (which launched/cratered spectacularly in February 2023). Since then a whole bunch of people have taken a swing at this problem, most notably Google Gemini and ChatGPT Search.

Those 2023-era versions were promising but very disappointing. They had a strong tendency to hallucinate details that weren’t present in the search results, to the point that you couldn’t trust anything they told you.

In this first half of 2025 I think these systems have finally crossed the line into being genuinely useful."

simonwillison.net/2025/Apr/21/

Simon Willison’s WeblogAI assisted search-based research actually works nowFor the past two and a half years the feature I’ve most wanted from LLMs is the ability to take on search-based research tasks on my behalf. We saw the …

"This course is intended to provide you with a comprehensive step-by-step understanding of how to engineer optimal prompts within Claude.

After completing this course, you will be able to:

- Master the basic structure of a good prompt
- Recognize common failure modes and learn the '80/20' techniques to address them
- Understand Claude's strengths and weaknesses
- Build strong prompts from scratch for common use cases

Course structure and content

This course is structured to allow you many chances to practice writing and troubleshooting prompts yourself. The course is broken up into 9 chapters with accompanying exercises, as well as an appendix of even more advanced methods. It is intended for you to work through the course in chapter order.

Each lesson has an "Example Playground" area at the bottom where you are free to experiment with the examples in the lesson and see for yourself how changing prompts can change Claude's responses. There is also an answer key.

Note: This tutorial uses our smallest, fastest, and cheapest model, Claude 3 Haiku. Anthropic has two other models, Claude 3 Sonnet and Claude 3 Opus, which are more intelligent than Haiku, with Opus being the most intelligent.

This tutorial also exists on Google Sheets using Anthropic's Claude for Sheets extension. We recommend using that version as it is more user friendly."

github.com/anthropics/courses/

"We must stop giving AI human traits. My first interaction with GPT-3 rather seriously annoyed me. It pretended to be a person. It said it had feelings, ambitions, even consciousness.

That’s no longer the default behaviour, thankfully. But the style of interaction — the eerily natural flow of conversation — remains intact. And that, too, is convincing. Too convincing.

We need to de-anthropomorphise AI. Now. Strip it of its human mask. This should be easy. Companies could remove all reference to emotion, judgement or cognitive processing on the part of the AI. In particular, it should respond factually without ever saying “I”, or “I feel that”… or “I am curious”.

Will it happen? I doubt it. It reminds me of another warning we’ve ignored for over 20 years: “We need to cut CO₂ emissions.” Look where that got us. But we must warn big tech companies of the dangers associated with the humanisation of AIs. They are unlikely to play ball, but they should, especially if they are serious about developing more ethical AIs.

For now, this is what I do (because I too often get this eerie feeling that I am talking to a synthetic human when using ChatGPT or Claude): I instruct my AI not to address me by name. I ask it to call itself AI, to speak in the third person, and to avoid emotional or cognitive terms.

If I am using voice chat, I ask the AI to use a flat prosody and speak a bit like a robot. It is actually quite fun and keeps us both in our comfort zone."

theconversation.com/we-need-to

The ConversationWe need to stop pretending AI is intelligent – here’s how
More from The Conversation UK

Ich hab gehört, im Fediverse interessieren sich ein paar Leute für #Digitalisierung und #IT?!
Gut zehn Minuten Eurer Zeit für die Masterarbeit eines Freundes: eine #Umfrage zu #KI und #Chatbots in der Kommunalverwaltung.
#Datenschutz, #Privatsphäre, #Usability - was ist Euch wichtig? Sagt es ihm für seine Studie ⤵️

hcicaachen.fra1.qualtrics.com/ Boosting is sharing! Für die Forschung! 😊

hcicaachen.fra1.qualtrics.comQualtrics Umfrage | Digitale Verwaltungsdienste und DatenschutzNimm an einer wissenschaftlichen Umfrage teil und teile deine Meinung zu digitalen Verwaltungsangeboten, Chatbots und Datenschutz in der öffentlichen Verwaltung.

"Dwarkesh Patel: I want to better understand how you think about that broader transformation. Before we do, the other really interesting part of your worldview is that you have longer timelines to get to AGI than most of the people in San Francisco who think about AI. When do you expect a drop-in remote worker replacement?

Ege Erdil: Maybe for me, that would be around 2045.

Dwarkesh Patel: Wow. Wait, and you?

Tamay Besiroglu: Again, I’m a little bit more bullish. I mean, it depends what you mean by “drop in remote worker“ and whether it’s able to do literally everything that can be done remotely, or do most things.

Ege Erdil: I’m saying literally everything.

Tamay Besiroglu: For literally everything. Just shade Ege’s predictions by five years or by 20% or something.

Dwarkesh Patel: Why? Because we’ve seen so much progress over even the last few years. We’ve gone from Chat GPT two years ago to now we have models that can literally do reasoning, are better coders than me, and I studied software engineering in college. I mean, I did become a podcaster, I’m not saying I’m the best coder in the world.

But if you made this much progress in the last two years, why would it take another 30 to get to full automation of remote work?

Ege Erdil: So I think that a lot of people have this intuition that progress has been very fast. They look at the trend lines and just extrapolate; obviously, it’s going to happen in, I don’t know, 2027 or 2030 or whatever. They’re just very bullish. And obviously, that’s not a thing you can literally do.

There isn’t a trend you can literally extrapolate of “when do we get to full automation?”. Because if you look at the fraction of the economy that is actually automated by AI, it’s very small. So if you just extrapolate that trend, which is something, say, Robin Hanson likes to do, you’re going to say, “well, it’s going to take centuries” or something."

dwarkesh.com/p/ege-tamay
#AI #LLM #Reasoning #Chatbots #AGI #Automation #Productivity

"It’s not that hard to build a fully functioning, code-editing agent.

It seems like it would be. When you look at an agent editing files, running commands, wriggling itself out of errors, retrying different strategies - it seems like there has to be a secret behind it.

There isn’t. It’s an LLM, a loop, and enough tokens. It’s what we’ve been saying on the podcast from the start. The rest, the stuff that makes Amp so addictive and impressive? Elbow grease.

But building a small and yet highly impressive agent doesn’t even require that. You can do it in less than 400 lines of code, most of which is boilerplate.

I’m going to show you how, right now. We’re going to write some code together and go from zero lines of code to “oh wow, this is… a game changer.”

I urge you to follow along. No, really. You might think you can just read this and that you don’t have to type out the code, but it’s less than 400 lines of code. I need you to feel how little code it is and I want you to see this with your own eyes in your own terminal in your own folders.

Here’s what we need:

- Go
- Anthropic API key that you set as an environment variable, ANTHROPIC_API_KEY"

ampcode.com/how-to-build-an-ag

ampcode.comHow To Build An Agent | AmpBuilding a fully functional, code-editing agent in less than 400 lines.

Ich finde es ja Klasse das wir immer wieder neue Technik einsetzen um den Kunden Service zu verbessern.

Außer die Technik funktioniert nicht richtig und dann sitz man da und hat gar keinen Ansprechpartner. Je mehr ich da Kontakt mit #ChatBots bekomme auch bei schöner 24/7 Erreichbarkeit desto mehr kotzt es mich an.

Das Beispiel hier Zeit das auch ChatBots sehr wohl das "Ja da kann ich jetzt auch nix machen, warten sie einfach ab" drauf haben. 1A echten Service nachgeahmt.

#CommunityContent

Wenn generative #Chatbots mit #Internetsuche falsche #Quellen zitieren und sich dabei sicher geben, wird es gefährlich. Eine Untersuchung des Tow Center for Digital Journalism hat acht KI-Suchmaschinen unter die Lupe genommen und geschaut, wie gut die KI-Syseme im Umgang mit Originalartikeln abschneiden.

#KI #Fehlinformation #Quellenangaben #Medienkompetenz #DigitaleRecherche #Faktenprüfung #Credits

tino-eberl.de/uncategorized/ki

Tino Eberl · KI-Suchmaschinen im Faktencheck: 60 % der Zitate sind falsch
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