Which intelligences do we need more of? (015)
Welcome to Artificial Insights: your weekly review of how to better collaborate with AI.
Nothing makes me appreciate the passing of time as much as routines. The weekly committment of sharing what I have learned about AI and developing an ongoing and public opinion about the state of development is a great reminder of how few days there actually are between one Monday and the following.
This week’s edition includes a handful of links to nuggets that will help you understand the quickly developing area of machine intelligence, from as many diverse perspectives as possible.
Last week I had the privilege of meeting a close friend and collaborator in Lisbon – our work together revolves around education and training – and it’s increasingly apparent how all forward-looking conversations today revolve around the inevitable development of AI. Maybe I am biased, but it is increasingly difficult to imagine a world where we define intelligence as something that happens only within yourself – rather it should be a measure of our ability to collaborate and grow with as many other intelligences as possible. We owe this to future generations.
Rolling Stone special with AI experts Joy Buolamwini, Safiya Noble, Rumman Chowdhury, Seeta Peña Gangadharan and Timnit Gebru. Each brings a distinct and complementary perspective about current developments in the AI industry and the implicit biases being perpetuated.
Today the risks of artificial intelligence are clear — but the warning signs have been there all along.
An index of resources, articles and big questions related to the development of AGI - will send you down more rabbit holes than you can imagine. Don’t miss the related HN discussion.
DW Documentary explores the future world of humanizing artificial intelligence, questioning boundaries of our mind, bodies and souls. I like how the journalist goes all-in by embodying robots and creating avatars, as well as talking to the technology creators. Some scenes caused discomfort, which I suppose is the intent.
Mo Gawdat interviewed by Peter Diamandis critiquing the current education system's outdated model and advocating for a shift towards AI and technology-centered learning. Whether AI will make its way into schools is undeniable - the question is how.
Machine learning technique that leverages knowledge acquired from one task to improve the performance on a different but related task. Typically, deep learning models are pre-trained on large-scale datasets for a specific task, such as image classification, where they learn general features and patterns. Instead of training a new model from scratch for another task, transfer learning allows us to use the knowledge gained from the pre-trained model as a starting point and fine-tune it for the new task using a smaller dataset. The idea behind transfer learning is that the features learned in lower layers of the pre-trained model are generic and can be applied to many different tasks.
Long Read from Substack
Many are exploring approaches for combining human and artificial intelligence in group workshops and training. If this is something you are interested in, you should consider joining the upcoming public demo of our AI-driven co-creation tool, Sandbox.
Sandbox allows workshop facilitators to integrate GPT into online or in-person exercises as "smart sticky notes". We are still learning where people's needs are, and would love to hear from people working in this space. If you're interested but unavailable on Sep 5 please DM me to schedule a 1:1 or learn more.
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Artificial Insights is written by Michell Zappa, CEO and founder of Envisioning, a technology research institute.
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