Max Tegmark argues that the downplaying is not accidental and threatens to delay, until it’s too late, the strict regulations needed.
Most of the deepfakes (videos with fake hyper-realistic recreations) generated by artificial intelligence (AI) that spread through social media feature political representatives and artists and are often linked to current news cycles.
From Google and OpenAI’s latest AI releases to Waymo notching 50K robotaxi rides a week, check out this week’s awesome tech stories from around the web.
New method turns liquid crystal elastomers into soft robotic actuators at room temperature, enabling easier customization and mass production.
Summary: Researchers developed a drone that flies autonomously using neuromorphic image processing, mimicking animal brains. This method significantly improves data processing speed and energy efficiency compared to traditional GPUs.
The study highlights the potential for tiny, agile drones for various applications. The neuromorphic approach allows the drone to process data up to 64 times faster while consuming three times less energy.
Championing an aerospace renaissance — elizabeth reynolds, managing director, US, starburst aerospace.
Elizabeth Reynolds is Managing Director, US of Starburst Aerospace (https://starburst.aero/), a global Aerospace and Defense (A\&D) startup accelerator and strategic advisory practice championing today’s aerospace renaissance, aligning early-stage technology innovators with government and commercial stakeholders and investors to modernize infrastructure in space, transportation, communications, and intelligence.
This video explores the 4th to the 10th dimensions of time. Watch this next video about the 10 stages of AI: • The 10 Stages of Artificial Intelligence.
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Aman Bhargava from Caltech and Cameron Witkowski from the University of Toronto to discuss their groundbreaking paper, “What’s the Magic Word? A Control Theory of LLM Prompting.” They frame LLM systems as discrete stochastic dynamical systems. This means they look at LLMs in a structured way, similar to how we analyze control systems in engineering. They explore the “reachable set” of outputs for an LLM. Essentially, this is the range of possible outputs the model can generate from a given starting point when influenced by different prompts. The research highlights that prompt engineering, or optimizing the input tokens, can significantly influence LLM outputs. They show that even short prompts can drastically alter the likelihood of specific outputs. Aman and Cameron’s work might be a boon for understanding and improving LLMs. They suggest that a deeper exploration of control theory concepts could lead to more reliable and capable language models.
Scientists pitted OpenAI and Meta chatbots against over 1,900 humans. The algorithms bested participants in areas like the detection of irony and faux pas.
New research says that quantifying progress in AI must account for the fact that the humans AI is measured against are actually a variable, noisy benchmark.
