What number's at its highest in 17 years? 8 out of 10 employers report difficulty filling key roles. What's the solution? Featured in @Forbes by @tynanwrites, our CFO @K3vinRubin talks #upskilling and #reskilling, which 71% of global orgs rely on. Read: https://
bit.ly/3Omh7uh
AI
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Employer Difficulty Filling Roles Reaches 17-Year High
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Maker Spotlight: Akshit Ireddy
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Maker Spotlight: Akshit Ireddy https://t.co/9Ro8ZS5nbc
— Cohere (@cohere) 3 août 2023Maker Spotlight: Akshit Ireddy
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Agent Retriever Tool Architecture for Decision-Making
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The basic idea: Give an agent a tool that is itself a retriever. The agent can then call this tool and get back a list of documents This allows the agent to decide when it wants to do retrieval – could do it once, twice, or not at all
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New Memory Type for Agent Tool Invocation Results
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We've also added a new type of memory This type of memory allows for using the results of previous tool invocations in future agent interactions This means if you ask a follow up question, you don't have to do retrieval all over again
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Smart Information Retrieval Strategies for AI Systems
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The benefits over normal retrieval include: – You don't do retrieval if the question isn't about the topic
– You don't do retrieval if the question is about previously mentioned topics
– You can do multiple retrieval steps
– You can retrieve from multiple sources -

Conversational Retrieval Agents Replace ConversationalRetrievalChain
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Conversational Retrieval Agents The most popular chain in @langchain is the ConversationalRetrievalChain, which allows you chat with your data Using an agent instead can allow for great flexibility, and its a narrow and well defined enough agent that its fairly reliable
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Conversational Retrieval Agents: Advanced QA Systems
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I'll dive into details in this thread, but quick links: Blog: https://
blog.langchain.dev/conversational
-retrieval-agents/
… Python Docs: https://
python.langchain.com/docs/use_cases
/question_answering/how_to/conversational_retrieval_agents
… JS Docs: https://
js.langchain.com/docs/use_cases
/question_answering/conversational_retrieval_agents
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Hugging Face Joins PyTorch Foundation as Premier Member
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Hugging Face is now part of the PyTorch Foundation as a premier member We have been collaborating with the PyTorch team for the past four years and are committed to supporting the project. We share an objective: to lower the barrier of entry to ML. https://
pytorch.org/blog/hugging-f
ace-joins/?hss_channel=tw-776585502606721024
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Open Source as a Solution to AI Challenges
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Can Open Source save AI? – GigaOm https://
bit.ly/3q54Yle
#AI #MachineLearning #DeepLearning #LLMs #DataScience