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Introducing Orangescrum Pages: a wiki and knowledge base that lives inside your project tool. Write, review and publish team knowledge next to your tasks. Share it on a public help portal. Let your AI assistant read it over MCP. 🧵 #KnowledgeBase #Wiki214477
🔍 ERC-20 is a technical standard used for all smart contracts on Ethereum. It has a list of rules that must be followed by the Ethereum-based tokens. ERC-20 defines six beneficial functions within the Ethereum system. #knowledgebase #crypto #ERC20 #smartcontract #ethereum
0120- 💸 Extra funding 💸 Experienced traders usually keep some extra funds on a separate balance. This allows to hedge the bets and average down if trades go the wrong way. #knowledgebase #margintrading #crypto
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Document360@document360Juggling between different platforms to gather your company knowledge might be daunting. With an #internalwiki, your employees can store all the information in one place and this helps to share and collaborate easily. #knowledgebase2119- 📈 Bullish Engulfing Pattern shows that buyers outnumber sellers. Here, a small red body of a candle is engulfed by the longer green body of the following candle, as bulls outpace bears. It results in a positive price change. #knowledgebase #crypto #trade
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Musheg Gevorgyan@mushgevChatGPT is impressive, but can AI answer domain-specific questions trained on your company data? The answer is yes, you will be able very soon! We are currently working on it and will announce our private beta very soon. Stay tuned! #chatgpt #generativeai #knowledgebase #data
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Pandora Chain@PandoraChain_#PandoraChain #KnowledgeBase 5. How does Pandora Chain's dual-token economic model work? Pandora Chain's model forms an efficient and propagable traffic incubator through open-source protocols, adapts to a variety of application scenarios, and achieves fair distribution of value.
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Control the quality of your wiki pages or increase trust in your #KnowledgeBase. Approve pages, assign approvers to categories, view your approval requests, see who approved what and when, and more. Check out our new #OpenSource #MediaWiki extension Page Approvals
03201.6K- Pandora Chain@PandoraChain_#PandoraChain #KnowledgeBase 10. How to access data on Pandora Chain? You can view the on-chain data of Pandora Chain on our blockchain explorer:
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The most common enterprise use of #LLMs is in building RAG (retrieval augmented generation) applications on an organization's own custom #KnowledgeBase, which are difficult to put in production. @AbacusAI addresses the key challenges for you. Find out how:
Abacus.AI @abacusaiThe most common use of LLMs in enterprise is building RAG (retrieval augmented generation) applications on a custom knowledge base, which are difficult to put in production. Some of the challenges are: •Parsing docs and PDFs (most open-source libraries struggle with this) •Data pipelines: the app should have access to updates on data •Custom front-ends: you would either want the app to be able to connect to teams or slack or have custom front end •Complex orchestration: the app should be able to coordinate between vector stores and doc retrievers and handle complex prompts •SQL and code execution: you may need to execute code depending on your application •LLM choice: you should be able to choose the right LLM for your specific use-case •Ease of iteration: you need to measure accuracy and iterate on the app We at have built many LLMs (and put them in production) that handle all these challenges. Our ChatLLM allows you to do all these within days.35824330.8K
Abacus.AI@abacusaiThe most common use of LLMs in enterprise is building RAG (retrieval augmented generation) applications on a custom knowledge base, which are difficult to put in production. Some of the challenges are: •Parsing docs and PDFs (most open-source libraries struggle with this) •Data pipelines: the app should have access to updates on data •Custom front-ends: you would either want the app to be able to connect to teams or slack or have custom front end •Complex orchestration: the app should be able to coordinate between vector stores and doc retrievers and handle complex prompts •SQL and code execution: you may need to execute code depending on your application •LLM choice: you should be able to choose the right LLM for your specific use-case •Ease of iteration: you need to measure accuracy and iterate on the app We at have built many LLMs (and put them in production) that handle all these challenges. Our ChatLLM allows you to do all these within days.
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Torium Network #KnowledgeBase Do you know that Torium Network's primary strategic partner is Veridian Systems, with whom they signed a US$1 million first-phase partnership? This strategic partnership enables Torium Network and Veridian Systems to bring "Scan & Earn" product verification and supply chain features into the Torium ecosystem, starting in Southeast Asia. Start Now - Invite Code - TORIUM-6DNRS9 $TOR #ToriumNetwork #Layer1 @ToriumNetwork @djmllssnHQ @FelixOkah
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Microsoft Azure@AzureDo you know how to build a #KnowledgeBase for your #QnA Maker Bot? Get the documentation:11827- Pandora Chain@PandoraChain_#PandoraChain #KnowledgeBase 6. What is Pandora Chain's incentive mechanism like? Pandora Chain designs a reasonable token economics and incentive mechanism that aim to encourage nodes to participate in network maintenance and verify transactions to maintain network sustainability and security.
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How many times a week do you answer a question you have answered before, and where does the answer live? #CustomerSupport #KnowledgeBase00118- 🔬 Research 🔬 Trading without proper research is something similar to gambling. Things may go your way a few times, but it will probably lead to significant losses in the long run. #margintrading #crypto #knowledgebase #cryptotrading
1229 - A common enterprise use of #LLMs is in RAG (Retrieval Augmented Generation) applications on an organization's own custom #KnowledgeBase. These are difficult to put in production. @AbacusAI #GenerativeAI handles it all for you. See how in the thread below:
Abacus.AI @abacusaiThe most common use of LLMs in enterprise is building RAG (retrieval augmented generation) applications on a custom knowledge base, which are difficult to put in production. Some of the challenges are: •Parsing docs and PDFs (most open-source libraries struggle with this) •Data pipelines: the app should have access to updates on data •Custom front-ends: you would either want the app to be able to connect to teams or slack or have custom front end •Complex orchestration: the app should be able to coordinate between vector stores and doc retrievers and handle complex prompts •SQL and code execution: you may need to execute code depending on your application •LLM choice: you should be able to choose the right LLM for your specific use-case •Ease of iteration: you need to measure accuracy and iterate on the app We at have built many LLMs (and put them in production) that handle all these challenges. Our ChatLLM allows you to do all these within days.014557.5K 
Just starting with #WordPress? Find help on how to build your website, create posts, maintain security, and manage the #website easily in our extensive #knowledgebase of articles and tutorials:
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ClickHelp.com@ClickHelpNews🚀 Building your fortress of knowledge? Document360 is a powerhouse—but it’s not your only option. We explored the 7 best alternatives to help your team grow smarter, faster, and more efficiently. Read more here: #TechDocs #SaaS #KnowledgeBase
161091- Your wiki should do more than store docs. With Orangescrum Pages, it can serve your customers, show you what is missing, and work with your AI assistant. 🧵 #KnowledgeBase #Wiki10138
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