9 #FutureofWork Trends For 2023 https://
gtnr.it/3v973eC
AI
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Langchain: Open-Source Framework Revolutionizing LLM Applications
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Meet Langchain, an AI-integrated open-source framework that aims to revolutionise LLM-based applications. The model can streamline projects, empower intelligent agents & unlock control over data processing. Tap here for more on its plan & execution- https://
rb.gy/qafs7 -
Broad AI: Multimodal Models Between Narrow and General Intelligence
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We are in neither ANI nor AGI. Multimodal multitasking models sit in between as broad AI. They cannot be narrow as they may perform more than 1 task but they are not equivalent to human brain https://
bbntimes.com/science/toward
s-broad-artificial-intelligence-ai-the-edge-in-2021
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Multimodal Transformers Represent Broad AI Not AGI
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Multi modal multi tasking Transformer models are neither narrow nor AGI. They are broad AI https://
bbntimes.com/science/toward
s-broad-artificial-intelligence-ai-the-edge-in-2021
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AI Researchers Survey on AGI Risk Probability Assessment
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These aren’t my words, 50% of AI researchers believes there is a 10% chance of it happening. Who else should we be listening to? https://
aiimpacts.org/2022-expert-su
rvey-on-progress-in-ai/
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Religious ChatGPTs: Exploring AI Applications in Faith
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That’s all for today folks! To read more about the uses of these religious ChatGPTs, follow https://
bit.ly/3MXkMiJ Share the thread with your fellow AI enthusiasts and stay tuned as we share more such interesting topics with you in the field of artificial intelligence. -
AI in Religious Research: Ethics and Compassionate Development
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Furthermore, utilizing AI for religious research could result in numerous positive and negative outcomes. Keeping all these in mind, we need to be very mindful and pave new developments in the field with the utmost compassion and for the greater good of humanity.Tweet your views!
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Ensuring Objective Data and Algorithms in AI Systems
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But it is imperative to keep this in mind and ensure that the data and algorithms used are objective, leaving no scope for biases. Do you agree?