“The most effective debugging tool is still careful thought, coupled with judiciously placed print statements.” — Brian Kernighan, co-creator of Unix
AI
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AI Investment Predictions for 2023 and Beyond
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What kinds of investments can we anticipate in the #AI space in 2023 and beyond? See what DataRobot CTO, Michael Schmidt, predicts for the future of AI on @wef . Read more
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LangChain Hub Makes Sharing Agents and Chains Easier
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This should make it easier than ever to share your chains/agents, which we think are much more useful than just prompts! See here for how to upload agents (
https://
github.com/hwchase17/lang
chain-hub/tree/master/agents
…) and here for how to upload chains (
https://
github.com/hwchase17/lang
chain-hub/tree/master/chains
…) -
Loading LangChain Agents with Self-Ask Search Tool
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To load agents: “`
from langchain.agents import initialize_agent agent = initialize_agent(tools, llm, agent="lc://agents/self-ask-with-search/agent.json")
“` Documentation: https://
langchain.readthedocs.io/en/latest/modu
les/agents/examples/load_from_hub.html
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LangChain SQL Agent Variants with Custom Parameters
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This makes it possible upload chains/agents that are variants of existing chains/agents but with different parameters For example, here's an agent specifically instructed to interact with SQL databases that @fpingham came up with: https://
github.com/hwchase17/lang
chain-hub/tree/master/agents/zero-shot-react-sql
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Loading Chains with LangChain Framework
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To load chains: “`
from langchain.chains import load_chain chain = load_chain('lc://chains/path/to/file.json')
“` Documentation: https://
langchain.readthedocs.io/en/latest/modu
les/chains/generic/from_hub.html
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LangChainHub Update: All Chains and Agents Now Available
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Big update to LangChainHub With lots of help from @sjwhitmore
, all chains and agents are now on there, and loadable in a single line of code Including some chains/agents not available in the python package -
AI Progress Unpredictability and Human Capability Assessment
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One lesson from AI progress is it’s hard to predict the relative difficulties of various skills; one lesson from AI limitations is that humans are much more capable than we give ourselves credit for.
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Meta Myths: Point by Point Affirmation Analysis
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Sounds like a point by point affirmation of Meta Myths
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Google LolNerf: Learn from One Look at Images
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Learn more about it here – https://
ai.googleblog.com/2022/09/lolner
f-learn-from-one-look.html
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