Category: Assistive Technologies

@BenPrystawski transmitting knowledge between generations, and over decades, by human memory, with noise

Ben Prystawski @BenPrystawski I’ll be presenting on “Cultural reinforcement learning: a framework for modeling cumulative culture on a limited channel” at 1:45 #cogsci2023 this afternoon! My talk will be in the “Culture and Language II” session. The paper is here if you’re interested: https://psyarxiv.com/q4tz8/ Replying to @BenPrystawski Ben, When I was a teenager about 60
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Google Research and Google itself – “open and transparent” would help

Google Research: Introducing PaLM 2, Google’s next generation large language model | Research Bytes at https://www.youtube.com/watch?v=yAANQypgOo8 I was head to head testing OpenAI and Bard. Bard is not even close. It simply refused to try. If you open Google research and operations, transparency might let the world see what you are doing, help you with plans,
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Richard Chats with OpenAI Chat GPT Plus 4.0 about electrons, gravity, and AIs compiling global issues

Richard: How many electrons moving at 110 km/second would be needed to have a total kinetic energy of 5.75E10 Joules? OpenAI ChatGPT Plus 4.0: The kinetic energy of a single particle can be calculated using the formula: KE = 0.5 * m * v^2 where: m = mass v = velocity For an electron, the
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Twitter Feryal Adaptive Reinforcement with XLand games, rather model human groups and speech

Feryal Behbahani at https://arxiv.org/search/cs?searchtype=author&query=Behbahani%2C+F Edan Meyer @ejmejm1 I totally forgot to post my recent video on AdA: https://youtu.be/BkWLCrLapQo Check it out if you want to see how @FeryalMP & colleagues successfully scale RL and pave the way towards future RL foundation models. It’s some great work! Human-Timescale Adaptation in an Open-Ended Task Space at https://arxiv.org/abs/2301.07608
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Richard Chats with Bard about Maxwell’s static and dynamic field equation and their relation to gravitational potential fields

Richard: I am reading Jackson’s “Classical Electrodynamics” again. Looking at the fundamental assumptions and limitations of his times. At the very beginning he is talking about electrostatic fields and he says Curl (E) = 0 and says “this is equivalent to saying that E is the gradient of a scalar electric potential” But soon he
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Twitter: Deep Mind – examine priorities

Google DeepMind @GoogleDeepMind Generating videos from text is challenging due to: 📈 High computational cost 📉 Limited quantities of high quality text-video data 📹 Variable videos lengths Here’s how the team addressed these issues when developing Phenaki: https://dpmd.ai/3O5U6vl Replying to @GoogleDeepMind Feed the hungry, train the jobless, comfort the helpless and lonely ones, watch out
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Richard Chats with Google Bard about probability preserving transformations, atoms, the vacuum, and the past

Richard: Can you help explain the Madelung energy and the heat of formation of ionic crystals? Bard: Sure. The Madelung energy is the electrostatic energy of interaction between the ions in an ionic crystal. It is named after Erwin Madelung, who first calculated it in 1919. The Madelung energy can be calculated using a series
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Richard Chats with OpenAI ChatGpt PLus 4.0 about magnetic fields, global experiments, gravitational correlation networks

Richard: There is an Ampere’s law for the integral of H on a boundary. When you write equations in this conversation, ALWAYS use the explicit multiplication symbol so I can clearly see the breaks between symbols. “*” OpenAI ChatGpt PLus 4.0: Ampere’s Law is a fundamental principle of electromagnetism that relates the integral of the
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