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I think that the amount of clean data is more important than the amount of parameters.
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GPT-3 Exploration Book One of the most wanted books in the world, now in your hands at a very reasonable price. $20 This book contains many information needed for work Ones understand the dangers of GPT-3 Chapter 2: Applications and Use Cases of GPT-3 technical requirements Understanding general GPT-3 use cases Presentation of the initiation of playground creation for text processing and categorization building tasks Text classification text Understand the semantic search summary Semantic search tool Getting started with GPT-3 Working with OpenAI Playground Technical requirements Explore the OpenAI Developer Console Developer documentation Developer resources accounts and institutions Pricing and billing Usage reports Member management Dig deeper into this field Choose the right engine response length Temperature and the penalty for repetition better than stop the sequence Enter the text and enter the restart text Show possibilities Work with presets Standard English Grammar for the system Unstructured data analysis summary Work with OpenAI API technical requirements Understanding APIs HTTP Recognition Uniform resource identifiers Methods HTTP text HTTP headers HTTP HTTP Response Status Codes Checklist OpenAI API endpoints Engine loopback engines Create a completed semantic search Serving CURL and Postman Understanding API authentication Keeping API keys private Submitting an authenticator request to the OpenAI API Working with multiple organizations Presenting JSON using a completion endpoint Using a semantic search endpoint summary Chapter 5: Call OpenAI API in code technical requirements to choose your programming language
Download Link: https://payhip.com/ExploringGPT
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GPT-3 Exploration Book One of the most wanted books in the world, now in your hands at a very reasonable price. $20 This book contains many information needed for work Ones understand the dangers of GPT-3 Chapter 2: Applications and Use Cases of GPT-3 technical requirements Understanding general GPT-3 use cases Presentation of the initiation of playground creation for text processing and categorization building tasks Text classification text Understand the semantic search summary Semantic search tool Getting started with GPT-3 Working with OpenAI Playground Technical requirements Explore the OpenAI Developer Console Developer documentation Developer resources accounts and institutions Pricing and billing Usage reports Member management Dig deeper into this field Choose the right engine response length Temperature and the penalty for repetition better than stop the sequence Enter the text and enter the restart text Show possibilities Work with presets Standard English Grammar for the system Unstructured data analysis summary Work with OpenAI API technical requirements Understanding APIs HTTP Recognition Uniform resource identifiers Methods HTTP text HTTP headers HTTP HTTP Response Status Codes Checklist OpenAI API endpoints Engine loopback engines Create a completed semantic search Serving CURL and Postman Understanding API authentication Keeping API keys private Submitting an authenticator request to the OpenAI API Working with multiple organizations Presenting JSON using a completion endpoint Using a semantic search endpoint summary Chapter 5: Call OpenAI API in code technical requirements to choose your programming language
Download Link: https://payhip.com/ExploringGPT
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Đăng ký tham gia ngay để tìm kiếm giải pháp cho sự nghiệp của mình: 📍 Link đăng ký: 📍 Thời gian: Thứ 6, 19h30-21h30, ngày 16/12/2022 📍 Hình thức: Online qua Zoom Meeting https://forms.gle/2Xp5anMY15hYnPrx5
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LEARN #EXCEL...START TODAY ON YOUTUBE.…👇 👇 https://youtube.com/playlist?list=PLJSCTuDCzml2bxuV0aI2MfPebMStaJcp4
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LEARN #EXCEL...START TODAY ON YOUTUBE.…👇 👇 https://youtube.com/playlist?list=PLJSCTuDCzml2bxuV0aI2MfPebMStaJcp4
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SpaceX landing is performed via Convex Optimization, circuits are designed with Discrete/ Convex Optimization, systems are verified with Formal Logic, Supply Chain Management is convex optimization ...Networking protocols is written with CS algorithms, but Optimization is coming to them. Compilers are formal languages. Real robots which manufacture things is physics and adaptive control.
Backend in most companies are algorithms in compiled languages(algorithms).
BlackRock uses typically stochastic control combined with extremely sophisticated math to control portfolios and it can be observed from several public scientists talks affilated with them.
I know some businesses is driven by AI like Ambarella, but this is small amount. I heard from friends that in usual companies (not social media or web crawling companies or companies which try to make ML and AI widely used like NVIDIA) datascience is used for not important tasks only, because some methods does not even have theory for covergrnce guarantees and to what algorithm converges which each engineer should have in mind.
In fields where people understand what they are doing they do not need AI. Of course a lot of people use Applied Math(AM) for model in their fields, and we can call fundamentals PDES as AI - I will not stop you.
But if you can not give garantees and competitive fields can - it maybe a trouble for application ML as I see it.
I am more than glad to know about usefull application of ML models in some businesses, but essential tasks is solved by logic, physics, geometry, algebra, crypto, etc. and optimization combines everything.
Probably we should isolate heuristics part - and improve that (plan A) or rename all applied math and physics and computer science into (AI) 😉
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Or maybe watch a documentary where animals live free instead of cages? 🤷🏾♀️
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Love it! Good explanation Senthil Ganesh Kuppuswamy sir . Thank you . I would like to join.
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good read...reposted with thanks...ezzat daniel nesseim on #ezzatdanielnesseim
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