HomeGoogle's Gems Offer a Gentle Start to AI Prompt Engineering
While I'm no sales expert, the advice seemed valuable. Having a transcript of the chat saved in the sidebar is a nice feature for reviewing the session later.
However, there are some limitations. The Gem maintains a consistent tone but doesn't refer back to earlier points in the conversation, only moving forward. In a real coaching session, you'd expect the coach to connect later discussions with earlier ones. This seems to be a broader issue with large language models, likely requiring better use of the context window.
Additionally, the Gem relies on general sales knowledge from its training data. For more focused use cases, it could benefit from retrieval-augmented generation (RAG), which would allow it to tap into external databases for domain-specific knowledge.
Another potential improvement could be storing simple background knowledge as sentences, similar to OpenAI's "memory" function. This would let users incorporate recurring facts into their chats without repeating them each time.
The most significant limitation is that Gems don't retain past conversations. Each time you use a Gem, it starts fresh, with no memory of previous sessions. This is a major drawback if you want to use the Gem repeatedly, as you can't build on past discussions.
Despite these shortcomings, Gems are a great way to get started with prompt engineering, especially for those new to the concept. They offer a practical introduction to crafting effective prompts and using Gen AI tools.
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Comments (58)
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![StevenGonzalez]()
이 글을 읽으니 AI 프롬프트를 더 잘 활용할 수 있을 것 같아요. 요즘 ChatGPT 사용할 때마다 제가 원하는 답변이 잘 안 나와서 고민이었는데, 구글이 제안하는 방법이 도움이 될까요? 🤔 실제로 적용해보고 결과를 비교해보고 싶네요!
![JackMartin]()
この記事、AIプロンプトエンジニアリングの基礎を優しく教えてくれるね。GoogleのGeminiを使いこなすコツが知りたかったからタイムリーだわ✨ でも、こういうスキルが必須になる未来って、逆にプロンプトが読めない人が取り残されないか心配…
![RaymondAllen]()
Prompt engineering sounds like trying to sweet-talk a robot into doing your homework! Google's Gems seem like a cool way to ease into it, but I wonder how much trial and error it takes to get it right. 🧠
![BillyThomas]()
Google's Gems me ha ayudado mucho a empezar con la ingeniería de prompts de IA. ¡Es como un empujoncito en la dirección correcta! Los ejemplos son súper útiles, pero a veces desearía tener más consejos avanzados para usuarios experimentados. Aún así, una gran herramienta para principiantes! 😊
![WillieAnderson]()
구글의 Gems는 정말로 프롬프트 엔지니어링을 시작하는 데 도움이 되었어요. 올바른 방향으로 부드럽게 안내하는 느낌이에요. 하지만 예시가 때때로 너무 기본적이라고 느껴질 때도 있어요. 그래도 AI 초보자에게는 좋은 출발점이에요! 🌟
![PeterJohnson]()
Google's Gems has really helped me get started with AI prompt engineering. It's like a gentle nudge in the right direction! The examples are super helpful, but sometimes I wish there were more advanced tips for seasoned users. Still, a great tool for beginners! 😊
While I'm no sales expert, the advice seemed valuable. Having a transcript of the chat saved in the sidebar is a nice feature for reviewing the session later.
However, there are some limitations. The Gem maintains a consistent tone but doesn't refer back to earlier points in the conversation, only moving forward. In a real coaching session, you'd expect the coach to connect later discussions with earlier ones. This seems to be a broader issue with large language models, likely requiring better use of the context window.
Additionally, the Gem relies on general sales knowledge from its training data. For more focused use cases, it could benefit from retrieval-augmented generation (RAG), which would allow it to tap into external databases for domain-specific knowledge.
Another potential improvement could be storing simple background knowledge as sentences, similar to OpenAI's "memory" function. This would let users incorporate recurring facts into their chats without repeating them each time.
The most significant limitation is that Gems don't retain past conversations. Each time you use a Gem, it starts fresh, with no memory of previous sessions. This is a major drawback if you want to use the Gem repeatedly, as you can't build on past discussions.
Despite these shortcomings, Gems are a great way to get started with prompt engineering, especially for those new to the concept. They offer a practical introduction to crafting effective prompts and using Gen AI tools.
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As AI-driven coding tools gain traction, Swedish startup Lovable has secured a major funding round. The company aims to raise $3 billion, potentially boosting its valuation to $13.2 billion—double the $6.6 billion recorded last December. Menlo Ventur
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이 글을 읽으니 AI 프롬프트를 더 잘 활용할 수 있을 것 같아요. 요즘 ChatGPT 사용할 때마다 제가 원하는 답변이 잘 안 나와서 고민이었는데, 구글이 제안하는 방법이 도움이 될까요? 🤔 실제로 적용해보고 결과를 비교해보고 싶네요!
この記事、AIプロンプトエンジニアリングの基礎を優しく教えてくれるね。GoogleのGeminiを使いこなすコツが知りたかったからタイムリーだわ✨ でも、こういうスキルが必須になる未来って、逆にプロンプトが読めない人が取り残されないか心配…
Prompt engineering sounds like trying to sweet-talk a robot into doing your homework! Google's Gems seem like a cool way to ease into it, but I wonder how much trial and error it takes to get it right. 🧠
Google's Gems me ha ayudado mucho a empezar con la ingeniería de prompts de IA. ¡Es como un empujoncito en la dirección correcta! Los ejemplos son súper útiles, pero a veces desearía tener más consejos avanzados para usuarios experimentados. Aún así, una gran herramienta para principiantes! 😊
구글의 Gems는 정말로 프롬프트 엔지니어링을 시작하는 데 도움이 되었어요. 올바른 방향으로 부드럽게 안내하는 느낌이에요. 하지만 예시가 때때로 너무 기본적이라고 느껴질 때도 있어요. 그래도 AI 초보자에게는 좋은 출발점이에요! 🌟
Google's Gems has really helped me get started with AI prompt engineering. It's like a gentle nudge in the right direction! The examples are super helpful, but sometimes I wish there were more advanced tips for seasoned users. Still, a great tool for beginners! 😊
