"an internet search engine that writes what it finds, but sometimes lies" is a pretty healthy mental model to have of ChatGPT to be honest (especially when you mix in Browse with Bing mode)
AGI
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Gemini Pro 1M Token Context Now Free Without Waitlist
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Gemini Pro with the 1 million token context limit is now available for free and without a waitlist! https://t.co/eiNsXCBMBU
— Simon Willison (@simonw) 10 avril 2024Gemini Pro with the 1 million token context limit is now available for free and without a waitlist!
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Three AI Trends Shaping the Future: Frontier Models and Autonomous Agents
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Three trends to watch that will shape the future of what AI will mean for us:
1) The unknown capabilities of frontier models
2) Growing evidence of "superhuman" LLM performance in some areas
3) Autonomous agents
Taken together, the implications are large. -
Elon predicts human-level AI by next year; major tech developments
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AI NEWS: Elon just predicted that AI may be smarter than any human by end of next year. Plus, more developments from Sam Altman, Canada/Justin Trudeau, Huawei, Cornell, Microsoft, Spotify, and Poe. Here's everything going on in AI right now:
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Multi-Model AI Orchestration Combining Claude GPT-4 Perplexity
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How does it work? The process is super simple. We simply query each model individually:
– Claude 3 Opus for reasoning + personality
– GPT-4 for reasoning
– PPLX for freshness/up-to-date info Then, Claude combines the strengths of each and responds with a final, ideal output. -
LLM Consciousness Claims: Evidential Value Compared to Dream Characters
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A claim of consciousness from an LLM has no more evidential value than the same from a character in a dream. The latter is more plausible a priori as the hardware is known to support it.
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The Future of Artificial General Intelligence AGI
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The future of Artificial General Intelligence (AGI)
by @antgrasso #MachineLearning #ArtificialIntelligence #Technology cc: @pascal_bornet @yvesmulkers @kuriharan -
Scale Explains Human Intelligence Across Domains Study
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Interesting paper argues that scale is all you need to explain humanity’s unique levels of intelligence. “We propose that global, genetic differences in learning and memory are sufficient to account for uniquely human reasoning across domains,” https://
nature.com/articles/s4415
9-024-00283-3
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Shared Attention Enables Collective Coordination and Knowledge Transfer
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People create fictitious entities, eg France, and are able through shared attention to teach others about these entities. Billions of people coordinate thanks to this. Shared attention also allows children to learn declarative knowledge, eg “what’s this blue thing dad?” Do our
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East Coast AI pragmatism overlooks risks of powerful systems
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I generally think the East Coast business attitude towards AI is healthy – I would characterize it as a focus on "what it can do" over "what does it all mean" – but it means that most large companies don't take the risk/possibilities of significantly more powerful AI seriously.