Anyway — back to building. AI delusions will still be prevalent next year, and the year after.
AI
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LLMs Lack Many Assumed Capabilities, Beware Hype
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Today, in 2023, it's good to remember that most of the capabilities that the tech industry assumes LLMs to already possess aren't yet within reach. Tread this space carefully, and beware of shiny demos. Last year, I was repeatedly told that the upcoming GPT-4 was already AGI.
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Domestic Robotics’ Unfulfilled Promises Before 2020
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Around that time, most people believed that domestic robotics would be a solved problem before 2020 (how could it not? did you see that Boston Dynamics video?), which led to a huge wave of investment in robotics — which of course didn't pan out.
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NIPS 2016 AGI Predictions on Reinforcement Learning
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Half of my conversations at NIPS 2016 were about how deep RL trained on game environments and infinite simulations would lead to AGI in 5-10 years (this was immediately post-Alpha Go).
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Human-level language understanding remains years away despite progress
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In 2016, when I tweeted that human-level language understanding was many years away (which is still the case now, though we're closer), mind the context: this was in response to many people, including prominent VCs, claiming that then-current AI was nearly there and was about to
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AI Progress: Applications vs Generality and Future Capabilities
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Remember — we are making progress on AI (though far more on applications than on generality, which remains largely a green field). The progress is significant in speed and magnitude. But the conventional wisdom of the tech community about current and near-future AI capabilities
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Good ideas copied: execution and structural advantage matter
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truth of doing great things: all the good ideas will be copied. it’ll always come down execution at the start, and structural advantage later on. unfortunately, competition is inescapable
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Artificial Intelligence: Blessing or Curse? Exploring AI’s Impact
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Artificial Intelligence: A Blessing Or A Curse?
#AI #AIio #BigData #ML #NLU #Futureofwork @gp_pulipaka @stratorob @PetiotEric @EvanKirstel @Fgraillot @HaroldSinnott @HeinzVHoenen @helene_wpli http://
ow.ly/KeRq30swnqk -
Multimodal LLM with Vision-Language Transformer and LangChain
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Using the `Vision-and-Language Transformer` model and @LangChainAI to create a Multimodal LLM in @Streamlit! 🔥
— Charly Wargnier (@DataChaz) 23 juillet 2023
– Demo app: https://t.co/miwwtiUxv0
– ViLT model: https://t.co/nz8npLUs9o
– App creator: @nicolas_tch pic.twitter.com/iTWuMwgc8WUsing the `Vision-and-Language Transformer` model and @langchain to create a Multimodal LLM in @Streamlit
! – Demo app: https://
vilt-gpt-ppn83ly4c9.streamlit.app
– ViLT model: https://
huggingface.co/dandelin/vilt-
b32-finetuned-vqa
…
– App creator: @nicolas_tch -
AI capability predictions: 2016 expectations versus 2023 reality
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In 2016, people didn't anticipate next-token prediction models (which were LSTMs then) to be this capable, but they did expect AI to soon have most of the capabilities they show now. Remember the chatbot mini-bubble of 2017? It was predicated on 2023 capabilities coming circa