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GPT Prompt Strategy: Brainstorm, Search, Hypothesize, and Refine - THIS is the FUTURE!!
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 GitHub: https://github.com/daveshap YouTube Transcript Downloader: https://github.com/daveshap/YouTubeChapterGenerator BSHR Loop: https://github.com/daveshap/BSHR_Loop
New Research: ChatGPT Can Design Computer Chips Faster
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TIMESTAMPS:
00:00 - Why to use ChatGPT for Chip Design?
01:26 - GPT for Chip Design Explained
06:13 - How to Train LLMs to Design Computer Chips
10:20 - Deepmind's Chip Designing AI Explained
12:10 - Other Companies & Stocks
The Paper: https://arxiv.org/abs/2309.10730
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Build AI agent workforce - Multi agent framework with MetaGPT & chatDev
Multi agent framework tutorial of MetaGPT & chatDev; Check the Hubspot x Jasper research of Using Generative AI to Scale Your Content Operations: https://offers.hubspot.com/generative-ai-for-content-operations?utm_source=youtube&utm_medium=social&utm_campaign=CR0087Sep2023_AIJason%2Fpartner_youtubeÂ
đ Links
- Follow me on twitter: https://twitter.com/jasonzhou1993
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- My discord: https://discord.gg/eZXprSaCDE
- chatDev: https://github.com/OpenBMB/ChatDev/tree/main
- MetaGPT: https://github.com/geekan/MetaGPT
- Agentverse: https://github.com/OpenBMB/AgentVerse
- Camel: https://github.com/camel-ai/camel
â±ïž Timestamps
0:00 Agent intro
1:22 Multi agent frameworks
2:38 chatDev
3:45 Scale your content operation with AI
4:27 Setup chatDev
7:11 How to customise
9:19 Customise roles
9:53 Customise phases
11:50 Customise chatChain
đđ» About Me
My name is Jason Zhou, a product designer who shares interesting AI experiments & products. Email me if you need help building AI apps! ask@ai-jason.com
#metagpt #aiagents #agents #gpt #autogpt #ai #artificialintelligence #tutorial #stepbystep #openai #llm #largelanguagemodels #largelanguagemodel #chatgpt #gpt4 #machinelearning
What is generative AI and how does it work? â with Mirella Lapata
How are technologies like ChatGPT created? And what does the future hold for AI language models?
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Watch the Q&A: https://youtu.be/9i2x2HyeW-Y
Generative AI refers to a type of artificial intelligence that involves creating new and original data or content. Unlike traditional AI models that rely on large datasets and algorithms to classify or predict outcomes, generative AI models are designed to learn the underlying patterns and structure of the data and generate novel outputs that mimic human creativity.
ChatGPT is perhaps the most well-known example, but the field is far larger and more varied than text generation. Other applications of generative AI include image and video synthesis, speech generation, music composition, and virtual reality.
In this lecture, Mirella Lapata will present an overview of this excitingâsometimes controversialâand rapidly evolving field.
Mirella Lapata is professor of natural language processing in the School of Informatics at the University of Edinburgh. Her research focuses on getting computers to understand, reason with, and generate natural language. She is the first recipient (2009) of the British Computer Society and Information Retrieval Specialist Group (BCS/IRSG) Karen Sparck Jones award and a Fellow of the Royal Society of Edinburgh, the ACL, and Academia Europaea.
This talk was filmed at the Royal Institution on 29th September 2023, in collaboration with the Alan Turing Institute.
00:00 Intro
2:38 Generative AI isnât new â so whatâs changed?
8:43 How did we get to ChatGPT?
12:38 How are Large Language Models created?
22:48 How good can a LLM become?
26:57 Unexpected effects of scaling up LLMs
28:05 How can ChatGPT meet the needs of humans?
32:30 Chat GPT demo
38:07 Are Language Models always right or fair?
40:21 The impact of LLMs on society
42:54 Is AI going to kill us all?
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GPT-4 Has Vision: I figured out what it could do
Email Subscribers get the list: https://gregkamradt.ck.page/b6630af43e
Outline
0:00 - Intro
1:16 - Describe
2:06 - Interpret
3:30 - Recommend
5:23 - Convert
7:23 - Extract
8:46 - Evaluate
10:45 - Assist
13:28 - Greg's Reflections
Gregâs Info:
- Twitter: https://tiny.one/VtxG3kC
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