prompting

OpenAI Publishes Prompting Guide for GPT-5.1

Good morning. It’s Monday, November seventeenth.On today in tech history: In 1995IBM researchers introduced Envelope Searcha brand new technique to speed up large-vocabulary speech recognition. It combined A* search’s ability to look ahead...

What My GPT Stylist Taught Me About Prompting Higher

TL;DR: I built a fun and flamboyant GPT stylist named Glitter—and by chance discovered a sandbox for studying LLM behavior. From hallucinated high heels to prompting rituals and emotional mirroring, here’s what I learned...

Programming Robots With Prompting

In partnership with Good morning. It’s Friday, February seventh.Did you realize: On at the present time in 1984, astronauts Bruce McCandless II and Robert L. Stewart conducted the primary untethered spacewalk...

Cognitive Prompting in LLMs

Can we teach machines to think like humans?Without cognitive prompting, the larger model scored about 87% on the maths problems. Once we added deterministic cognitive prompting (where the model followed a hard and fast...

Anthropic Shares Top Suggestions For Prompting

Good morning. It’s Monday, April ninth.Did you recognize: On at the present time in 1995, the Sony PlayStation was introduced in North America? Anthropic AI’s Prompting Suggestions GPT-Next Dates...

Optimize LLM with DSPy : A Step-by-Step Guide to construct, optimize, and evaluate AI systems

Because the capabilities of huge language models (LLMs) proceed to expand, developing robust AI systems that leverage their potential has turn out to be increasingly complex. Conventional approaches often involve intricate prompting techniques, data...

Creating Synthetic User Research: Using Persona Prompting and Autonomous Agents

The method begins with scaffolding the autonomous agents using Autogen, a tool that simplifies the creation and orchestration of those digital personas. We will install the autogen pypi package using pypip install pyautogenFormat the...

Achieving Structured Reasoning with LLMs in Chaotic Contexts with Thread of Thought Prompting and Parallel Knowledge Graph Retrieval

Large language models (LLMs) demonstrated impressive few-shot learning capabilities, rapidly adapting to latest tasks with only a handful of examples.Nonetheless, despite their advances, LLMs still face limitations in complex reasoning involving chaotic contexts overloaded...

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