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We've added a new "reasoning" focus (beta) on Perplexity for Pro users. It will use the new OpenAI o1-mini. There is no search integration yet. The model is slow, and usage is limited because of rate limits. It is good for puzzles, math, and coding. Pro searches are your...

288,789 просмотров • 1 год назад •via X (Twitter)

Комментарии: 10

Фото профиля Aravind Srinivas
Aravind Srinivas1 год назад

10 uses/day

Фото профиля Mohamed
Mohamed1 год назад

Just want you to know i discovered Perplexity from your Lex interview and it has become my favorite company in the world at the moment. Your UI, UX, direct answers, rabbit hole chases, and your marketing are all incredible. Keep it up!

Фото профиля Intellectus Partners
Intellectus Partners1 год назад

Very cool @AravSrinivas we love the speed of iteration. It’s insanely good!!

Фото профиля Matt
Matt1 год назад

Is it an in house model or based off of o1?

Фото профиля Aravind Srinivas
Aravind Srinivas1 год назад

It’s literally just o1

Фото профиля Sagar Patil
Sagar Patil1 год назад

Genuine question: OpenAI just announced new rate limits for o1-mini. 50 messages a day. Why would someone use perplexity (o1-mini) if it doesn't have search integration?

Фото профиля Samar Singh
Samar Singh1 год назад

@youdotcom has it and integrated with search as well.

Фото профиля Marvin Baumann
Marvin Baumann1 год назад

@perplexity_ai For research purposes on different topics, do you recommend the large perplexity model or the Anthropic model and why?

Фото профиля Seth Rose
Seth Rose1 год назад

Everyone immediately typing "How many r's are in the word 'strawberry'." 🙄

Фото профиля arun
arun1 год назад

love this from the team!

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OpenAI just announced API access to o1 (advanced reasoning model) yesterday. I'm delighted to announce today a new short course, Reasoning with o1, built with OpenAI, and taught by Colin Jarvis, Head of AI Solutions at OpenAI, to show you how to use this effectively! Unlike previous language models which generate output directly, o1 “thinks before it responds,” and generates many reasoning tokens before returning a more thoughtful and accurate response. It is great at complex reasoning -- including planning for agentic workflows, coding, and domain-specific reasoning in STEM fields like law. But how you should use it is quite different from other LLMs. I think o1 will be a game changer for many AI applications; and in this course, you'll learn how to use it effectively. In detail, you’ll: - Learn to recognize what tasks o1 is suited for, and when to use a smaller model, or combine o1 with a smaller model - Understand the new principles of prompting reasoning models: Be simple and direct; no explicit chain-of-thought required; use structure; show rather than tell - Implement multi-step orchestration in which o1 plans, and hands tasks over to gpt-4o-mini to execute specific steps; this illustrates a design pattern to optimize intelligence (accuracy) and cost - Use o1 for a coding task to build a new application, edit existing code, and test performance by running a coding competition between o1-mini and GPT 4o - Use o1 for image understanding and learn how it performs better with a "hierarchy of reasoning," in which it incurs the latency and cost upfront, preprocessing the image and indexing it with rich details so it can be used for Q&A later - Learn a technique called meta-prompting, in which you use o1 to improve your prompts. Using a customer support evaluation set, you'll iteratively use o1 to modify a prompt to improve performance You'll also learn about how OpenAI used reinforcement learning to produce a model that uses "test-time compute" to improve performance. I think you'll find this course enjoyable and valuable. Please sign up for it here:

Andrew Ng

357,401 просмотров • 1 год назад